Mathematical and theoretical biology

Mathematical and theoretical biology is an interdisciplinary field that applies mathematical techniques and theoretical approaches to understand biological systems and processes. This area of research is diverse, encompassing various aspects of biology, from ecology and evolutionary biology to population dynamics, epidemiology, and cellular biology. ### Key Components: 1. **Mathematical Modeling**: - Researchers create mathematical models to describe biological processes. These models can take various forms, including differential equations, stochastic models, and discrete models.

Bioinformatics is an interdisciplinary field that combines biology, computer science, mathematics, and statistics to analyze and interpret biological data. It plays a crucial role in managing and understanding the vast amounts of information generated by modern biological research, particularly in areas such as genomics, proteomics, and molecular biology.

Biobanks are repositories that store biological samples, such as blood, urine, DNA, and tissue, along with associated health and demographic information from donors. These collections are used for research purposes, primarily in the fields of genetics, medicine, and public health. The aim of biobanks is to facilitate studies that can lead to advancements in understanding diseases, developing new treatments, and improving overall healthcare.

Bioinformaticians are professionals who apply computational techniques and tools to analyze and interpret biological data. Their work often involves the integration of biology, computer science, mathematics, and statistics to solve complex problems related to biological systems and processes. Key responsibilities of bioinformaticians typically include: 1. **Data Analysis**: Processing and analyzing large sets of biological data, such as genomic sequences, protein structures, and metabolic pathways.

Bioinformatics and computational biology are interdisciplinary fields that combine biology, computer science, and mathematics to analyze and interpret biological data. Journals in this area publish research articles, reviews, and methodologies that advance our understanding and application of these fields. ### Bioinformatics: Bioinformatics primarily focuses on the development and application of computational tools and techniques for managing and analyzing biological data. This often involves sequence analysis, genomics, proteomics, systems biology, and data mining in biological research.

Bioinformatics organizations focus on the field of bioinformatics, which combines biology, computer science, and information technology to analyze and interpret biological data. These organizations may be involved in various activities, including research, development of software and tools, data analysis, and promoting education and collaboration in the field of bioinformatics. Here are some key aspects and types of bioinformatics organizations: 1. **Professional Societies**: Organizations that support professionals in bioinformatics through networking, conferences, and publication opportunities.

Bioinformatics software refers to a range of computational tools and applications designed to analyze, interpret, and visualize biological data. It plays a crucial role in the field of bioinformatics, which integrates biology, computer science, and information technology to manage and analyze biological information, particularly in genomics, proteomics, and molecular biology.

Biological databases are organized collections of biological data that are stored and managed to facilitate their retrieval and analysis. They are crucial in the fields of bioinformatics, genomics, proteomics, and other areas of biological research, providing researchers with easy access to vast amounts of information. Key features of biological databases include: 1. **Data Types**: Biological databases may contain various types of data, such as DNA sequences, protein sequences, gene annotations, metabolic pathways, structural data, and experimental results.

Biological sequence format refers to the standardized ways of representing biological sequences, such as DNA, RNA, or protein sequences, in a textual format that can be easily read, shared, and analyzed by computational tools and biologists. Different formats serve various purposes and can include information about the sequence, annotations, and metadata. Some common biological sequence formats include: 1. **FASTA Format**: This is one of the most widely used formats for representing nucleotide or protein sequences.

Biomedical informatics journals are academic publications that focus on the application of informatics in the fields of biology, medicine, and healthcare. These journals cover a wide range of topics, including but not limited to: 1. **Health Information Systems**: Studies on electronic health records (EHRs), health information exchanges (HIEs), and other digital systems used in healthcare.

Biorepositories, also known as biobanks, are facilities or collections that store biological samples, such as human tissue, blood, DNA, and other bodily fluids, as well as associated data. These samples are collected and stored for future research purposes, particularly in the fields of medicine, genetics, and biotechnology. Key aspects of biorepositories include: 1. **Sample Collection and Storage**: Biorepositories collect samples from donors, which may include healthy individuals or patients with specific conditions.

Evolutionary computation is a subset of artificial intelligence and computational intelligence that involves algorithms inspired by the principles of natural evolution. These algorithms are used to solve optimization problems and to find solutions to complex tasks by mimicking processes observed in biological evolution, such as selection, mutation, crossover, and inheritance. Key concepts in evolutionary computation include: 1. **Population**: A collection of candidate solutions to the problem being addressed.

Microarrays, also known as DNA chips or biochips, are technology platforms used to analyze the expression of many genes simultaneously or to genotype multiple regions of a genome. They consist of a small solid surface, typically a glass or silicon chip, onto which thousands of microscopic spots containing specific DNA sequences (probes) are fixed in an orderly grid pattern.

"Omics" is a term that encompasses a variety of fields of study that involve analyzing biological molecules on a large scale. It is derived from the suffix "-ome," which denotes a comprehensive collection or system. The most common omics disciplines include: 1. **Genomics**: The study of the genome, which is the complete set of DNA within an organism, including its genes and non-coding sequences.

Phylogenetics is a field of biology that studies the evolutionary relationships among various biological species or entities based on their physical and genetic characteristics. This discipline primarily uses the concept of a phylogenetic tree, a diagram that represents the evolutionary pathways and relationships among different organisms, showing how they diverged from common ancestors over time.

Structural bioinformatics is a specialized branch of bioinformatics that focuses on the analysis and prediction of the three-dimensional structures of biological macromolecules, primarily proteins and nucleic acids (like DNA and RNA). It combines concepts from biology, chemistry, computer science, and information technology to understand the structure-function relationships of biological molecules.

The 100,000 Genomes Project was an initiative in the United Kingdom aimed at sequencing the genomes of 100,000 individuals, primarily focusing on patients with rare diseases and their families, as well as cancer patients. Launched in 2012 and coordinated by Genomics England, the project sought to harness the power of genomic data to improve the understanding of genetic conditions and drive advancements in personalized medicine.

The 1000 Genomes Project was an international research effort aimed at providing a comprehensive resource for understanding human genetic variation. Launched in 2008 and completed in 2015, the project aimed to sequence the genomes of at least 1,000 individuals from different populations around the world to catalog the genetic diversity present in human populations.

3D-Jury is a software application designed to facilitate the assessment and evaluation of projects in a three-dimensional space. It is often used in fields such as architecture, urban planning, and design to allow multiple stakeholders to review and provide feedback on 3D models or visualizations of projects. The platform enables users to interact with and manipulate 3D representations of projects collaboratively, which can enhance communication and decision-making during the project development process.

The ABCD Schema is a framework often used in the field of education and instructional design to create clear and measurable learning objectives. It stands for: 1. **A - Audience**: Identifies who the learners or participants will be. For example, "students," "employees," or "participants in a workshop." 2. **B - Behavior**: Specifies what the learner will be able to do after the instruction.

ANOVA-simultaneous component analysis (ASCA) is a statistical method that combines analysis of variance (ANOVA) with principal component analysis (PCA) for the analysis of high-dimensional data, particularly in the context of multivariate datasets. ### Key Features of ASCA: 1. **Purpose**: ASCA aims to identify and visualize the differences between groups while reducing the complexity of the data.

In bioinformatics, an accession number is a unique identifier assigned to a specific biological sequence or data entry in various databases, such as nucleotide and protein sequence databases. This identifier allows researchers to easily reference, retrieve, and share specific sequences or data associated with biological research. Accession numbers are commonly used in databases like: 1. **GenBank**: A nucleotide sequence database maintained by the National Center for Biotechnology Information (NCBI). 2. **EMBL**: The European Molecular Biology Laboratory database.

The Actino-ugpB RNA motif is a type of RNA sequence that has been identified in certain bacteria, particularly within the phylum Actinobacteria. It is a conserved structural element that is thought to play a role in the regulation of gene expression. Typically, RNA motifs like Actino-ugpB can function as riboswitches or regulatory elements that respond to specific metabolites or environmental conditions to modulate the activity of nearby genes.

Algae DNA barcoding is a molecular technology used to identify and classify algal species based on short, standardized sequences of genetic material, typically from specific regions of their DNA.

Align-m is a tool or framework designed for aligning machine learning models with specific tasks or goals. It could involve tasks such as improving the performance, interpretability, or robustness of these models. The precise functionality and applications of Align-m might vary based on the context in which it's used, such as whether it's in the realm of natural language processing, computer vision, or other areas of artificial intelligence.

Alignment-free sequence analysis is a computational approach used in bioinformatics to compare biological sequences, such as DNA, RNA, or proteins, without the need to align them in a traditional sense. In conventional sequence alignment (like global or local alignment), sequences are arranged to identify regions of similarity, which can be computationally intensive and may be biased by gaps and mismatches.

Automated species identification is a technological approach that utilizes various methods and tools to quickly and accurately identify different species of organisms—such as plants, animals, fungi, and microbes—without the need for manual classification by experts. This process often incorporates various technologies, including: 1. **Image Recognition**: Machine learning algorithms and computer vision techniques analyze images of specimens, comparing them to large databases of known species to determine an appropriate match.

The BED file format (Browser Extensible Data) is a text-based file format used primarily to store information about genomic regions. It is widely utilized in bioinformatics, particularly in the analysis and visualization of genomic data. Here are some key features and characteristics of the BED file format: 1. **Basic Structure**: BED files are typically tab-delimited and consist of at least three required fields: - **Chromosome**: The name of the chromosome or contig (e.g.

BIOSCI, which stands for Biological Sciences Electronic Communication Network, was an online discussion platform and a mailing list that facilitated communication among professionals in the biological sciences. It was a place for researchers, educators, and practitioners to share information, ask questions, and discuss various topics related to biology and life sciences.

A Backbone-dependent rotamer library is a collection of pre-computed side-chain conformations (rotamers) for amino acids that take into account the influence of the protein backbone on the orientation and flexibility of the side chains. In protein structures, the side-chain conformation of amino acids can be significantly affected by their environment, particularly by the dihedral angles of the backbone.

The Basel Computational Biology Conference is a scientific conference that focuses on advancements and developments in computational biology, a field that combines elements of biology, computer science, mathematics, and engineering. The conference typically brings together researchers, practitioners, and students to discuss topics such as bioinformatics, systems biology, computational genomics, and related areas. Participants often present their latest research findings, engage in discussions, and attend workshops and keynote lectures from leading experts in the field.

The Benjamin Franklin Award in Bioinformatics is an honor presented by the International Society for Computational Biology (ISCB). Established to recognize outstanding contributions in the field of bioinformatics, the award is named after Benjamin Franklin, the American polymath known for his contributions to science, among other fields. This award is typically given to individuals who have made significant advancements in bioinformatics research, which encompasses the development and application of computational tools to understand biological data.

Biclustering, also known as co-clustering or simultaneous clustering, is a data analysis technique that seeks to uncover patterns in data sets where both rows and columns are clustered simultaneously. Unlike traditional clustering methods, which typically group either rows (observations) or columns (features) independently, biclustering allows for the identification of subsets of data that exhibit similar characteristics across both dimensions.

Binning in metagenomics refers to the process of grouping or categorizing DNA sequences obtained from metagenomic studies into distinct bins that correspond to specific genomes or taxonomic groups. This is important because metagenomic data often come from environmental samples, where multiple microorganisms coexist, making it challenging to analyze the genetic material as a cohesive unit.

BioCreative is an international community and series of scientific challenges focused on the intersection of biology and computer science, particularly in the fields of text mining and biomedical data analysis. The main goal of BioCreative is to encourage the development of algorithms, tools, and methodologies for extracting valuable information from biological literature and other biological data sources.

BioMOBY (Bio Molecular Open Worlds Wide) is a framework designed for the integration and sharing of biological data and services over the internet. It aims to facilitate the discovery and retrieval of biological data from various sources by providing a standardized protocol for communication between different data providers, tools, and services in the life sciences domain.

BioPAX (Biological Pathway Exchange) is a standard format designed for the exchange, sharing, and representation of biological pathway information. It aims to enable interoperability among software and databases that manage biological data related to molecular interactions, cellular processes, and metabolic pathways. BioPAX provides a standardized vocabulary and structure for depicting biological entities—such as genes, proteins, and small molecules—and their interactions or relationships within biological pathways.

BioSimGrid is a bioinformatics infrastructure that focuses on providing a platform for the storage, sharing, and analysis of biological simulation data. It facilitates the management of large datasets generated from various biological simulations, including molecular dynamics simulations and other computational biology applications. Key features of BioSimGrid may include: 1. **Data Storage**: It offers a structured way to store simulation data, making it easy for researchers to access and retrieve large datasets.

Bioimage informatics is an interdisciplinary field that combines biology, computer science, and imaging technologies to analyze and interpret biological images. This area of research focuses on developing algorithms, software, and analytical methods to process and extract meaningful information from images captured in various biological contexts, such as microscopy, medical imaging, and even satellite imagery of ecosystems.

The Bioinformatics Institute (BII) is a research institute located in Singapore that focuses on bioinformatics and computational biology. It is part of the Agency for Science, Technology and Research (A*STAR), which is a major research and development organization in Singapore. Established in 2001, the BII's mission is to leverage computational methods and biological data to address scientific questions in biology and medicine.

The Bioinformatics Open Source Conference (BOSC) is an event focused on the open-source aspects of bioinformatics, emphasizing collaboration, sharing of tools, and methodologies within the bioinformatics community. It typically features presentations, workshops, and discussions on a variety of topics related to bioinformatics software, data analysis, and computational biology.

Bioinformatics discovery of non-coding RNAs (ncRNAs) refers to the computational methods and tools used to identify and characterize RNA molecules that do not code for proteins but have important biological functions. Non-coding RNAs include a diverse group of RNA types such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), small interfering RNAs (siRNAs), and ribosomal RNAs (rRNAs), among others.

Biological data refers to any data that is derived from biological systems, organisms, or processes. It encompasses a wide range of information related to the structure, function, and interactions of biological molecules, cells, tissues, organisms, and ecosystems. This type of data can be collected from various sources and can be used for a multitude of research and application purposes, including genomics, proteomics, ecology, medicine, and more.

Biological data visualization is a field that focuses on the graphical representation of biological data to facilitate understanding, analysis, and interpretation of complex biological phenomena. This process leverages various visualization techniques and tools to display the intricate patterns, structures, and relationships found in biological research, which can encompass a wide range of topics, including genomics, proteomics, metabolomics, ecological studies, and more.

A biological network is a conceptual and computational framework used to represent and analyze the complex interactions and relationships among various biological entities within an organism or biological system. These entities can include genes, proteins, metabolites, cells, and even entire organisms. Biological networks can take various forms, depending on the type of interactions being represented. Some common types of biological networks include: 1. **Gene Regulatory Networks**: These networks illustrate how genes regulate each other's expression through transcription factors and other regulatory molecules.

Biological network inference is the process of deducing or reconstructing biological networks from experimental data. These networks can represent various biological interactions and relationships, such as gene regulatory networks, protein-protein interaction networks, metabolic networks, and others. The goal of network inference is to understand the complex interactions that govern biological processes by creating models that illustrate how different components (genes, proteins, metabolites, etc.) interact with each other.

Biomedical text mining is an interdisciplinary field that applies techniques from natural language processing (NLP), machine learning, data mining, and information retrieval to extract valuable information and knowledge from vast amounts of unstructured biomedical literature and data. This field focuses primarily on the literature related to biology and medicine, which includes research articles, clinical notes, electronic health records, and other biomedical texts.

Biomimetics, also known as biomimicry or bioinspiration, is a field of study that seeks to emulate or draw inspiration from nature’s designs, processes, and systems to solve human challenges. It involves observing the structures, functions, and strategies found in biological organisms and ecosystems and translating those insights into innovative technologies and solutions. The goal of biomimetics is to create sustainable and efficient designs, often in areas such as materials science, engineering, robotics, medicine, and architecture.

Biopunk is a subgenre of speculative fiction that explores the implications and consequences of biotechnology, genetic engineering, and synthetic biology. It often focuses on themes such as the manipulation of living organisms, the ethical dilemmas of genetic modification, and the societal impacts of biotechnological advancements. In biopunk narratives, you might find elements such as: 1. **Genetic Engineering**: The modification of organisms at the genetic level, often highlighting the potential benefits and dangers involved.

Biositemap is not a widely recognized term or concept in standard references or topics familiar up until October 2023. However, it can be inferred that it may refer to a tool, system, or concept related to biological data, mapping of biological features, or a representation of biological information in a specified format.

Bloom filters are a probabilistic data structure used for efficiently testing whether an element is a member of a set. They are particularly useful in scenarios where space efficiency is a priority and where false positives are acceptable but false negatives are not. In the context of bioinformatics, Bloom filters have several important applications, including: 1. **Sequence Data Handling**: With the massive amounts of genomic and metagenomic data generated by sequencing technologies, storage and processing efficiency is paramount.

Brain mapping is a multidisciplinary field that involves the study and mapping of the anatomy and functions of the brain. It encompasses a variety of techniques and methods used to visualize and understand the brain's structure, connectivity, and activity. Brain mapping can be applied in both research and clinical settings.

C17orf75, or "Chromosome 17 Open Reading Frame 75," is a gene located on chromosome 17. It encodes a protein whose specific function is not fully understood. Like many other genes, it may play various roles in cellular processes, but detailed studies regarding its biological significance, potential associations with diseases, or mechanisms of action are still ongoing. As with many genes, research evolves, and new findings could shed light on its roles in human health or disease.

CAFASP (Critical Assessment of Fully Automated Structure Prediction) is a series of competitions designed to evaluate the performance of computational methods for predicting protein structures. It focuses on fully automated approaches, where participants submit their computational predictions of protein structures, which are then compared to experimentally determined structures. CAFASP aims to advance the field by providing a standardized way to assess the effectiveness of different algorithms and techniques in protein structure prediction. It helps researchers identify strengths, weaknesses, and areas for improvement in their methods.

CAMEO3D (Computer Aided Modeling of Earth Objects in 3D) is a 3D modeling system developed for creating and visualizing spatial data. It is primarily used in the fields of geology, planetary science, and related disciplines to model planetary surfaces and features based on various data sources, including satellite imagery and topographical data. The system allows scientists and researchers to create detailed three-dimensional representations of celestial bodies, which can facilitate analysis and interpretation of geological processes and features.

CASP can refer to several things, depending on the context. Below are a few of the most common meanings: 1. **Certified Advanced Security Practitioner (CASP)**: In the field of information technology, CASP is a certification offered by CompTIA. It is designed for advanced IT professionals who want to demonstrate their skills in enterprise security, risk management, and advanced security solutions.

The CIT Program Tumor Identity Cards refer to a specific initiative related to cancer diagnostics and patient care. CIT stands for "Cancer Identification Tools," and the program focuses on creating a personalized approach for identifying and managing tumors in patients. This entails developing tumor identity cards that help in the precise classification of cancer types based on molecular and genetic characteristics. These identity cards serve a crucial purpose in helping healthcare professionals understand the specific genetic makeup of a patient's tumor, which can influence treatment decisions and improve outcomes.

CRAM is a compressed file format used to store genomic data, particularly sequencing data generated by technologies like next-generation sequencing (NGS). It is designed to provide efficient storage and transfer of large amounts of biological data, especially in the context of DNA sequencing. ### Key Features of CRAM: 1. **Compression**: CRAM employs various compression techniques to reduce the size of genomic data compared to other formats like SAM (Sequence Alignment Map) and BAM (Binary Alignment Map).

CaBIG, which stands for the Cancer Biomedical Informatics Grid, is an initiative developed by the National Cancer Institute (NCI) in the United States. Launched in the early 2000s, the goal of CaBIG is to enhance cancer research by facilitating collaboration and data sharing among researchers, institutions, and healthcare organizations.

Canadian Bioinformatics Workshops (CBW) is an initiative aimed at providing training and resources in bioinformatics to researchers and students in Canada and beyond. These workshops typically cover a wide range of topics within the field, including but not limited to data analysis, software tools, programming languages, and various bioinformatics applications in genomics and proteomics. CBW is often organized by institutions, universities, or research groups and may feature hands-on, practical training sessions led by experts in the field.

The term "cellular model" can refer to different concepts depending on the context in which it is used. Here are a few common interpretations: 1. **Cellular Automata**: In mathematics and computer science, a cellular automaton is a discrete model studied in computational theory. It consists of a grid of cells, each of which can be in a finite number of states (often just "alive" or "dead").

A Chip Description File (CDF) is a critical component in semiconductor design and fabrication. It generally serves as a file that contains the descriptions of the characteristics of a chip or integrated circuit (IC) design. Here are key aspects related to Chip Description Files: 1. **Standardization**: CDFs help standardize how chip parameters and features are described, making it easier for designers, engineers, and manufacturing teams to understand the specifications of a given chip.

The Chou–Fasman method is a classical algorithm used for predicting the secondary structure of proteins based on their amino acid sequences. Developed by Paul Chou and George D. Fasman in the late 1970s, this method employs the properties of specific amino acids to forecast potential helical, sheet, and other secondary structural elements in a protein.

ClearVolume is an open-source visualization tool designed for the interactive analysis of large 3D volumetric datasets, such as those produced in scientific fields like biology, physics, and medicine. It typically provides features for volume rendering, manipulation, and exploration of volumetric data. Key functionalities of ClearVolume often include: 1. **Real-time Rendering**: It allows users to visualize 3D volumes in real time, making it easier to analyze complex data.

CodonCode Aligner is a software application used in the field of bioinformatics for the analysis and management of DNA and protein sequences. It is particularly designed for tasks such as the assembly and alignment of DNA sequences from various sources, including capillary and next-generation sequencing data. The software offers several key features: 1. **Sequence Assembly:** CodonCode Aligner can assemble overlapping DNA sequences to create a complete representation of a sequence. This is particularly useful for sequencing projects involving multiple fragments.

Computational epigenetics is an interdisciplinary field that combines principles from computational biology, bioinformatics, and epigenetics to analyze and interpret complex biological data related to epigenetic modifications. Epigenetics refers to the study of heritable changes in gene expression that do not involve changes to the underlying DNA sequence. These changes can be influenced by various factors, including environmental stimuli, lifestyle, and developmental processes.

Computational genomics is a field of study that combines computer science, statistics, mathematics, and biology to analyze and interpret genomic data. It involves the development and application of algorithms, software tools, and models to understand the structure, function, evolution, and regulation of genomes. Key aspects of computational genomics include: 1. **Data Analysis**: Processing and analyzing large-scale genomic data generated by high-throughput sequencing technologies. This includes DNA, RNA, and epigenomic data.

Computational immunology is an interdisciplinary field that applies computational techniques and quantitative analysis to understand, model, and predict immune system behaviors and interactions. It combines principles from biology, immunology, computer science, mathematics, and statistics to facilitate research and advancements in immunological studies. Key components of computational immunology include: 1. **Modeling Immune Responses**: Creating mathematical and computational models to simulate how the immune system responds to various pathogens, vaccines, and immune therapies.

The Computer Atlas of Surface Topography of Proteins (CASTp) is a computational tool and database designed to analyze the surface topology of proteins. It provides detailed information about the surface characteristics of protein structures, including information about cavities, channels, and pockets on protein surfaces. CASTp uses algorithms to identify and characterize these topographical features based on the three-dimensional coordinates of protein structures, typically derived from X-ray crystallography, NMR spectroscopy, or computational modeling.

The Conference on Semantics in Healthcare and Life Sciences (CSHALS) is an academic and professional event that focuses on the application of semantic technologies in the fields of healthcare and life sciences. The conference typically brings together researchers, practitioners, and industry stakeholders to discuss the latest developments, research findings, and innovations related to semantic web technologies, knowledge representation, data interoperability, and data analytics within these domains.

Consed is a software application used primarily for the editing and visualization of DNA sequence data, particularly in the context of genome assembly and analysis. It is designed to assist researchers in reviewing and refining sequence assemblies by providing tools for displaying sequence alignments, viewing quality scores, and facilitating the identification of errors or gaps in the sequence data.

A consensus sequence is a sequence of nucleotides (in DNA or RNA) or amino acids (in proteins) that represents the most common or shared residue found at each position in a multiple sequence alignment. It highlights the most typical or representative features of a set of sequences that may demonstrate variability at each position. In the context of molecular biology, consensus sequences are often used to identify conserved regions that may be critical for function, such as binding sites for proteins or essential motifs within DNA regulatory regions.

"Contact order" can refer to different concepts depending on the context, but it is often associated with legal or social settings, particularly in the context of family law or child custody arrangements. Here are the primary meanings: 1. **Family Law Context**: In custody disputes, a contact order is a legal decision made by a court that outlines the terms under which a non-custodial parent can have contact with their child.

Critical Assessment of Function Annotation (CAFA) is an evaluation initiative designed to assess the accuracy and effectiveness of computational methods for predicting the function of proteins. Established in 2010, CAFA serves as a benchmark for evaluating how well computational models can predict biological functions based on sequence or structural data. The main aspects of CAFA include: 1. **Data Input**: The initiative uses a large set of proteins with well-characterized functions.

The Critical Assessment of Genome Interpretation (CAGI) is an initiative designed to evaluate and improve methods for interpreting genomic data, particularly in the context of genetic variants associated with human diseases. CAGI brings together researchers, clinicians, and bioinformaticians to assess the accuracy and reliability of computational tools and frameworks used to predict the phenotypic effects of genetic variations.

DIMPL stands for "Dynamic Inter-Molecular Potential Library." It is a computational physics framework used for simulating molecular interactions and dynamics through various potential energy functions. DIMPL allows researchers and scientists to model complex molecular systems and study their properties by providing a flexible platform for implementing different types of potentials, including those used in molecular simulation and computational chemistry.

DNA and RNA codon tables are essential tools in molecular biology that summarize the relationships between sequences of nucleotides and the amino acids they encode during the process of protein synthesis.

DNA barcoding in diet assessment is a molecular technique used to identify and analyze the dietary components of an organism’s diet by analyzing the DNA sequences of the consumed food items. This method provides a more accurate and sensitive means of identifying prey or food sources compared to traditional methods that often rely on morphological identification.

A DNA binding site refers to a specific region on the DNA molecule where proteins, such as transcription factors, enzymes, and other regulatory proteins, attach to the DNA. These sites are typically characterized by specific nucleotide sequences that are recognized and bound by these proteins, facilitating various biological processes such as gene regulation, DNA replication, repair, and chromatin remodeling.

A DNA microarray, also known as a gene chip or DNA chip, is a powerful tool used in molecular biology and genetics for the simultaneous analysis of thousands of genes. It consists of a small solid surface—typically a glass slide or a silicon chip—that has been populated with numerous DNA probes. Each probe is a short, single-stranded nucleic acid that is complementary to a specific DNA sequence corresponding to a gene of interest.

DNA read errors refer to inaccuracies that occur when DNA sequences are read or interpreted during various sequencing processes. When scientists analyze genetic material, they rely on DNA sequencing technologies to generate digital representations of the sequences. However, these technologies can sometimes produce errors due to various factors, such as: 1. **Sequencing Technology**: Different sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) have varying error rates and types.

DREAM Challenges is an initiative that aims to accelerate discoveries in biomedical research by inviting the scientific community to collaborate on predictive modeling and data analysis challenges. These challenges often focus on specific problems in areas such as genomics, drug discovery, disease research, and other health-related fields. Participants are typically provided with datasets related to a particular challenge and are encouraged to develop and test algorithms or models that can address specific scientific questions or predictions.

Darwin Core is a standard used for sharing and publishing biodiversity data. It provides a structured framework for the exchange of information related to biological diversity, including species occurrence data, taxonomic classifications, and other related environmental information. Darwin Core was created to improve the interoperability of biodiversity data across different systems and organizations. It consists of a set of terms and definitions, enabling biodiversity datasets to be easily shared and understood by researchers, conservationists, and policymakers globally.

The Darwin Core Archive (DwC Archive) is a data standard used for sharing biodiversity data. It is part of the Darwin Core standards, which provide a framework for providing information about biological diversity in a structured and interoperable way. The Darwin Core Archive facilitates the sharing and publishing of biodiversity datasets, particularly in the context of specimen records, observations, or related data concerning organisms. It consists of various types of metadata and data files that collectively allow for the easy exchange and usage of biodiversity information.

The DeLano Award for Computational Biosciences is an award that recognizes outstanding contributions and achievements in the field of computational biosciences. Named after Dr. Warren DeLano, a prominent scientist known for his work in molecular modeling and computational biology, the award commemorates innovative research and development that employs computational techniques to advance our understanding of biological systems and processes.

De novo protein structure prediction refers to the process of predicting the three-dimensional (3D) structure of a protein solely from its amino acid sequence, without using any information from homologous protein structures. This method relies on computational algorithms and models to simulate the physical and chemical principles governing protein folding, allowing researchers to make educated guesses about how a protein will fold into its functional form.

De novo transcriptome assembly is the process of reconstructing the complete set of RNA transcripts in a given organism or sample without prior reference to a known genome. This is particularly useful in situations where the genome of the organism is not available, poorly annotated, or when studying non-model organisms. Here are the key steps and concepts involved in de novo transcriptome assembly: 1. **RNA Extraction**: First, RNA is extracted from the cells or tissues of interest.

Demographic and Health Surveys (DHS) are extensive surveys that collect data on population, health, and nutrition indicators in developing countries. They are designed to provide high-quality and nationally representative data that are essential for policymakers, researchers, and program managers in the fields of public health, demographic studies, and development planning.

Digital phenotyping is a research method that involves the use of data collected from personal digital devices, such as smartphones, wearables, and other digital technologies, to assess and analyze an individual's behaviors, activities, and experiences. This approach aims to provide insights into an individual's health and well-being by capturing real-time, continuous data that reflects their psychological and physical states.

Digital transcriptome subtraction (DTS) is a computational technique used in bioinformatics and molecular biology to identify and differentiate between RNA transcripts that are present in a given sample. This method involves comparing the transcriptome of a particular sample against a reference transcriptome to subtract out unwanted or irrelevant transcripts, thereby highlighting specific transcripts of interest.

Direct Coupling Analysis (DCA) is a computational technique used in various fields such as biology, particularly in the analysis of protein structures and interactions, as well as in machine learning and statistics. In the context of protein science, DCA is used to identify and model the interactions between different residues in a protein sequence. The primary goal is to discern which amino acids are directly coupled to each other through evolutionary relationships.

The Distributed Annotation System (DAS) is a framework designed for the efficient integration and sharing of biological data, particularly annotations related to genomic features. DAS allows for the distribution and retrieval of biological data from multiple sources, enabling researchers to work with various datasets seamlessly. ### Key Components of DAS: 1. **Data Sources**: DAS servers host biological data and provide it through a standardized protocol. These servers can contain various types of data, including gene annotations, sequence information, and protein structures.

Do-it-yourself biology, often abbreviated as DIY biology or simply DIY bio, is a community-driven movement that encourages individuals and small groups to conduct biological research or experiments outside traditional academic and commercial labs. This grassroots approach democratizes access to biotechnology and biological experimentation, allowing hobbyists, students, and citizen scientists to explore biological concepts and innovate in various fields like genetics, microbiology, and synthetic biology.

Docking, in the context of molecular biology and chemistry, refers to a computational technique used to predict and analyze the interactions between two molecules, typically a small molecule (ligand) and a larger molecule, often a protein or nucleic acid (receptor). The primary objective of docking is to identify the preferred orientation and affinity of the ligand when it binds to the receptor, which can be crucial for drug discovery and development.

In bioinformatics, a dot plot is a graphical method used to visualize the similarities and differences between two biological sequences, such as DNA, RNA, or protein sequences. The primary purpose of a dot plot is to identify regions of similarity that may indicate homology, structural or functional relationships, or conserved sequences. ### How Dot Plots Work: 1. **Matrix Representation**: In a dot plot, one sequence is represented along the x-axis and the other along the y-axis.

A "dry lab" generally refers to a type of laboratory or research environment that focuses on computational and theoretical work rather than hands-on experimental work with physical materials. In a dry lab, researchers typically engage in activities such as: 1. **Computer Simulations**: Running simulations to model physical, chemical, biological, or engineering processes. 2. **Data Analysis**: Analyzing existing data sets, such as genomic data in bioinformatics or simulation results in physics.

A dual-flashlight plot is a visualization technique used in statistical analysis, particularly in the fields of genomics and bioinformatics. The term is often associated with the display of two-dimensional data sets, particularly in the context of visualizing relationships between variables or categories. In a dual-flashlight plot, two sets of data or two variables are represented on a two-dimensional axis, allowing for the comparison of their distributions, correlations, or other relationships.

The term "EMBRACE" can refer to a variety of things depending on the context. It could be an acronym for specific initiatives, programs, or terms in different fields, such as healthcare, education, or technology. For example, in healthcare, EMBRACE could refer to a specific program aimed at improving maternal and child health.

EVA, or Economic Value Added, is a financial performance metric that measures a company's ability to generate value above its cost of capital. It is often used as a benchmark to assess the profitability and efficiency of a company's operations. The concept was popularized by Stern Stewart & Co. in the 1990s.

Echinobase is a specialized database focused on echinoderm biology, providing a platform for researchers to access information about echinoderms, which include sea urchins, starfish, and sea cucumbers. The database typically includes genetic, genomic, and ecological data, as well as information about species distribution, developmental biology, and evolutionary relationships among echinoderms.

As of my last knowledge update in October 2021, "Endemixit" does not appear to refer to any widely recognized concept, brand, or term. It's possible that it could be a new product, concept, or term that has emerged after that date.

Engineering biology is an interdisciplinary field that combines principles of biology, engineering, and computational sciences to design and manipulate biological systems for various applications. It encompasses a broad range of activities, including the development of synthetic biological systems, the design of new organisms, and the manipulation of existing biological functions for practical uses. Key aspects of engineering biology include: 1. **Synthetic Biology**: This involves designing and constructing new biological parts, devices, and systems, as well as redesigning existing biological systems for useful purposes.

The Ensembl Genome Database Project is a major initiative aimed at providing a comprehensive and integrated source of genomic information for a variety of species. It is a joint project between the European Bioinformatics Institute (EBI) and the Wellcome Sanger Institute, and it provides a framework for the storage and analysis of genomic data.

The European Conference on Computational Biology (ECCB) is a prominent scientific conference that focuses on the field of computational biology, bioinformatics, and related areas. It serves as a platform for researchers, scientists, and professionals to share their latest findings, technologies, methodologies, and advancements in the computational analysis of biological data. Typically, the conference includes various components such as keynote lectures, oral presentations, poster sessions, and workshops.

The European Data Format (EDF) is a file format used for storing and sharing time-series data, particularly for biological and physiological signals, such as electroencephalograms (EEGs), electromyograms (EMGs), and other biomedical measurements. EDF was developed to facilitate the exchange of data between different systems and software tools. Key features of the EDF include: 1. **Standardization**: EDF provides a standardized way of representing data, which helps ensure compatibility between different devices and software applications.

Evolution@Home is a scientific research initiative that aims to study evolutionary processes using distributed computing. Participants can contribute their personal computing power to run simulations and experiments that model evolutionary dynamics, such as natural selection, population genetics, and species interactions. By leveraging the power of many individual computers, researchers can conduct large-scale simulations that would be impractical to run on a single machine. This collaborative approach allows for the gathering of significant amounts of data, facilitating a deeper understanding of evolutionary principles and processes.

ExPASy, or the Expert Protein Analysis System, is a bioinformatics resource portal operated by the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and tools for protein sequence analysis and functional annotation.

FASTA format is a text-based format for representing nucleotide or protein sequences. It is widely used in bioinformatics for storing and sharing biological sequences. The format was developed in the mid-1980s for use in sequence alignment software and has since become a standard format for sequence data. A FASTA file typically includes the following: 1. **Header Line**: The first line begins with a greater-than sign (`>`) followed by a sequence identifier and an optional description.

FASTQ is a standard file format used for storing biological sequence data, particularly nucleotide sequences from high-throughput sequencing technologies. It is commonly used in genomics and bioinformatics for representing raw sequence reads along with their associated quality scores. A FASTQ file consists of four lines for each sequence entry: 1. **Sequence Identifier Line**: Starts with an "@" symbol followed by a unique identifier for the sequence. It may also include additional information such as the name of the sequencing machine.

As of my last update in October 2023, there isn't a widely recognized service or product specifically named "FastContact." However, it's possible that it could refer to a variety of things such as a software application, a service related to contact management, or a feature within a broader platform focused on facilitating communication or connectivity.

Fast statistical alignment is a computational method used in bioinformatics for aligning biological sequences, such as DNA, RNA, or protein sequences, quickly and efficiently. This technique is particularly useful when dealing with large datasets or when rapid results are needed for applications like phylogenetic analysis, comparative genomics, or sequence searching.

Fish DNA barcoding is a genetic method used to identify and classify fish species based on a short, standardized region of their DNA. This technique leverages a specific gene, often a segment of the mitochondrial cytochrome c oxidase subunit I (COI) gene, to create a "bar code" unique to each species. The primary goal of fish DNA barcoding is to provide a reliable and efficient means of species identification, especially for those that might be difficult to distinguish morphologically.

Flow Cytometry Standard (FCS) is a file format specifically designed for storing the results of flow cytometry experiments. Flow cytometry is a biophysical technology used to analyze the physical and chemical characteristics of particles, typically cells, in a fluid as they pass through a laser. The FCS file format was developed to facilitate the exchange of flow cytometry data between different instruments and software.

Flow cytometry bioinformatics refers to the application of computational and statistical methods to analyze data generated from flow cytometry experiments. Flow cytometry is a powerful technique used to measure the physical and chemical characteristics of cells or particles as they flow in a fluid stream through a laser. This technology allows for the analysis of multiple parameters (e.g., size, complexity, and specific markers) of thousands of cells per second.

Flux balance analysis (FBA) is a mathematical approach used in systems biology to analyze the flow of metabolites through metabolic networks. It is particularly useful for studying the metabolic pathways of microorganisms and for understanding how cells allocate resources between various biochemical processes. ### Key Features of Flux Balance Analysis: 1. **Metabolic Network Representation**: - Metabolic networks are typically represented as stoichiometric matrices, where the rows correspond to metabolites and the columns correspond to reactions.

Fluxomics is a sub-discipline of metabolomics that focuses on studying the rates of metabolic reactions within a biological system. It aims to measure and analyze the flow of metabolites through various metabolic pathways to understand how cells and organisms produce and utilize energy and biomass. By examining fluxes rather than just the concentrations of metabolites, fluxomics provides insights into metabolic dynamics, regulation, and interactions among metabolic pathways.

The Foundational Model of Anatomy (FMA) is a comprehensive, detailed representation of human anatomy that provides a structured, navigable framework for understanding the relationships between anatomical structures. Developed at the University of Washington, the FMA incorporates information from various anatomical sources to create a high-quality, evolving digital resource that serves both educational and research purposes.

Fungal DNA barcoding is a method used to identify and classify fungal species based on specific sequences of DNA that are unique to each species. The technique typically employs short, standardized regions of the genome, known as barcode regions, which can be amplified and sequenced to provide a "fingerprint" for each fungal organism.

GC skew is a metric used to analyze the relative abundance of guanine (G) and cytosine (C) nucleotides in a segment of DNA. It is calculated to identify regions of DNA that may differ in their GC content, which can have implications for understanding genomic features, such as replication origins, gene density, and overall genomic stability.

GFP-cDNA refers to a complementary DNA (cDNA) that encodes the green fluorescent protein (GFP). GFP is a bioluminescent protein originally found in the jellyfish *Aequorea victoria*, and it emits a bright green fluorescence when exposed to ultraviolet or blue light. In molecular biology, cDNA is synthesized from messenger RNA (mRNA) through a process called reverse transcription.

GISAID, which stands for the Global Initiative on Sharing All Influenza Data, is a platform that promotes the sharing of genetic and epidemiological data related to influenza viruses and, more recently, coronaviruses, including SARS-CoV-2, the virus responsible for COVID-19. Launched in 2008, GISAID aims to facilitate rapid access to genomic data during public health emergencies, enhance global surveillance of infectious diseases, and improve preparedness for future outbreaks.

GLIMMER is a tool designed for gene prediction in genomic sequences. Specifically, it employs statistical algorithms based on hidden Markov models (HMMs) to identify genes in DNA sequences. Developed by Burge and Karlin in the late 1990s, GLIMMER has been used extensively in the annotation of genomes, especially for prokaryotic organisms like bacteria.

The GOR method, which stands for Gas-Oil Ratio method, is primarily used in petroleum engineering to evaluate reservoirs and estimate the performance of oil and gas wells. The gas-oil ratio (GOR) is defined as the volume of gas that is produced per unit of oil and is typically expressed in standard cubic feet of gas per barrel of oil (scf/bbl).

GenBank is a comprehensive public database that houses a vast collection of nucleotide sequences and their corresponding protein translations. It is maintained by the National Center for Biotechnology Information (NCBI) in the United States. GenBank serves as a crucial resource for researchers and scientists, providing access to sequences from a wide array of organisms, including bacteria, plants, animals, and viruses.

Gene Designer is a software application developed for the design and analysis of biological sequences, particularly for synthetic biology and genetic engineering. It provides tools for researchers and scientists to create, visualize, and simulate gene constructs, allowing them to design DNA sequences for various purposes, such as creating genetically modified organisms, developing gene therapies, and engineering proteins with desired properties.

Gene Ontology (GO) Term Enrichment is a statistical analysis technique used to determine whether specific biological processes, cellular components, or molecular functions are overrepresented (enriched) or underrepresented in a particular set of genes or gene products compared to a broader reference set, usually the entire genome or a specific biological context. The Gene Ontology project provides a comprehensive vocabulary to describe gene product attributes across all species.

A gene co-expression network is a biological network that represents the relationship between genes based on their expression levels across different conditions, time points, or samples. In such a network, nodes represent genes, and edges (connections between nodes) indicate a correlation or co-expression between those genes. ### Key Features of Gene Co-expression Networks: 1. **Nodes and Edges**: - **Nodes**: Each node in the network corresponds to a specific gene.

Gene Set Enrichment Analysis (GSEA) is a computational method used to identify whether a predefined set of genes shows statistically significant differences in expression under different biological conditions, such as diseased versus healthy states or various treatments. The goal of GSEA is to determine whether genes that share common biological functions, chromosomal locations, or regulation are overrepresented (enriched) within a specific group of genes that have been identified as being significantly different between conditions.

Gene Transfer Format (GTF) is a file format used for storing information about gene structure and annotations. It is commonly used in bioinformatics, particularly in the context of representing genomic annotations for genes, transcripts, and other features. GTF is often seen in conjunction with the Gene Expression Omnibus (GEO) and is especially related to the analysis of RNA-Seq data. A GTF file consists of a series of lines, each representing a different feature of a genome.

The General Data Format for Biomedical Signals (GDF) is a standardized file format designed for the storage and exchange of biomedical signals. It provides a structured way to represent various types of physiological signals, such as electroencephalograms (EEG), electromyograms (EMG), and other biomedical data. The main purpose of the GDF format is to facilitate interoperability between different software tools and systems used in biomedical research and clinical practice.

The General Feature Format (GFF) is a file format used for describing the features of biological sequences, such as genes and their various elements. It is widely utilized in bioinformatics for the annotation of genomic data and can accommodate diverse types of information related to sequence features. The GFF format consists of a series of lines, each representing a single feature, with fields separated by tabs.