Enhance Your Learning with Bioinformatics Flash Cards for quick understanding
The interdisciplinary field that combines biology, computer science, and statistics to analyze and interpret biological data.
The study of an organism's complete set of DNA, including genes and non-coding regions, to understand its structure, function, and evolution.
The large-scale study of proteins, including their structures, functions, and interactions, to gain insights into biological processes and diseases.
The study of an organism's complete set of RNA transcripts, including mRNA, to understand gene expression patterns and regulation.
The comprehensive analysis of small molecules, such as metabolites, in biological samples to understand metabolic pathways and their regulation.
The study of the three-dimensional structures of biological macromolecules, such as proteins and nucleic acids, and their interactions.
The process of arranging two or more DNA, RNA, or protein sequences to identify regions of similarity and infer evolutionary relationships.
The study of evolutionary relationships among organisms based on genetic data, often represented using phylogenetic trees.
The study of how genes are transcribed and translated into functional proteins, often using techniques like microarrays or RNA sequencing.
Repositories of biological data, such as DNA sequences, protein structures, and gene annotations, used for research and analysis.
Computational methods and techniques used to analyze biological data, such as sequence alignment algorithms or protein structure prediction algorithms.
The application of machine learning algorithms and statistical models to analyze and interpret biological data, such as predicting protein structures or identifying disease biomarkers.
The study of biological systems as integrated networks of genes, proteins, and other molecules, aiming to understand their behavior and function.
The use of bioinformatics tools and techniques to identify potential drug targets, design new drugs, and optimize drug efficacy and safety.
The consideration of ethical, legal, and social implications of bioinformatics research and applications, such as privacy concerns or data sharing policies.
The process of reconstructing a complete DNA sequence from shorter fragments, often obtained through DNA sequencing technologies.
A computational method to predict the three-dimensional structure of a protein based on its sequence similarity to experimentally determined structures.
High-throughput DNA sequencing technologies that enable rapid and cost-effective sequencing of large genomes or transcriptomes.
The physical contacts and associations between proteins, which play crucial roles in cellular processes and can be studied using experimental or computational methods.
A standardized vocabulary and hierarchical framework for annotating genes and their products with functional terms, facilitating biological interpretation.
The study of genetic material recovered directly from environmental samples, providing insights into microbial communities and their functions.
The study of how an individual's genetic makeup influences their response to drugs, aiming to personalize medicine and optimize drug therapies.
The computational prediction of a protein's three-dimensional structure based on its amino acid sequence, often using comparative modeling or ab initio methods.
The complex interactions and relationships between genes and their regulatory elements, which control gene expression and cellular processes.
The study of interconnected biochemical reactions and pathways in an organism's metabolism, often using computational models and simulations.
A computational method to identify and characterize the three-dimensional arrangement of atoms in a molecule that is responsible for its biological activity.
The process by which a protein adopts its functional three-dimensional structure, often guided by the protein's amino acid sequence and physical interactions.
The measurement of gene expression levels for thousands of genes simultaneously, providing insights into cellular processes and disease mechanisms.
The process of inferring the evolutionary relationships among a group of organisms based on genetic data, often represented using tree-like diagrams.
The prediction of the three-dimensional structure of a protein complex formed by the interaction of two or more proteins, often using computational methods.
The optimization of cellular metabolic pathways to produce valuable compounds, such as biofuels or pharmaceuticals, using genetic and computational approaches.
The study of evolutionary relationships among organisms based on genetic data, often involving the construction and analysis of phylogenetic trees.
The process of comparing and aligning the three-dimensional structures of proteins to identify similarities and differences, often used for functional annotation.
The construction and analysis of mathematical models to simulate and predict metabolic behavior and phenotypes of organisms, often using constraint-based approaches.
The study of how drugs are absorbed, distributed, metabolized, and eliminated by the body, aiming to optimize drug dosage and administration.
The computational prediction of a protein's function based on its sequence or structure, often using sequence homology or structural similarity methods.
A statistical method to determine whether a predefined set of genes shows statistically significant differences in expression between different biological conditions.
The process of inferring the complete set of metabolic reactions and pathways in an organism, often using genomic and biochemical data.
A computational method to screen large chemical libraries and identify potential drug candidates based on their similarity to a pharmacophore model.
The prediction of the three-dimensional structure of a protein complex formed by the interaction of two or more proteins, often using computational methods.
The control of gene expression levels and patterns by various regulatory mechanisms, such as transcription factors or epigenetic modifications.
The study of genetic material recovered directly from environmental samples, providing insights into microbial diversity, functions, and interactions.
The use of genetic information to predict an individual's response to specific drugs, aiming to personalize drug therapies and minimize adverse effects.
The assessment of the quality and reliability of a predicted or experimentally determined protein structure, often using various validation criteria and tools.
The computational prediction of gene regulatory interactions and networks based on gene expression data, aiming to understand cellular processes and disease mechanisms.
The process of identifying and characterizing small molecules, such as metabolites, in biological samples, often using mass spectrometry and database matching.
The graphical representation of evolutionary relationships among a group of organisms based on genetic data, often using tree-like diagrams.
Computational approaches and algorithms used to predict the three-dimensional structure of a protein based on its amino acid sequence and known structures.
The measurement and estimation of gene expression levels, often using techniques like reverse transcription polymerase chain reaction (RT-PCR) or RNA sequencing.
Computational algorithms and methods used to infer the evolutionary relationships among a group of organisms based on genetic data.
The graphical representation and visualization of the three-dimensional structure of a protein, often using molecular graphics software or web-based tools.
Experimental and computational techniques used to study gene expression patterns and regulation, such as microarrays, RNA sequencing, or quantitative PCR.
The statistical and computational analysis of evolutionary relationships among a group of organisms based on genetic data, often involving tree-building algorithms.
Software and web-based tools that utilize computational algorithms to predict the three-dimensional structure of a protein based on its amino acid sequence.
Experimental techniques and platforms used to measure gene expression levels for thousands of genes simultaneously, such as microarrays or RNA sequencing.
Software and web-based tools that enable the graphical representation and visualization of evolutionary relationships among a group of organisms based on genetic data.
The computational prediction of physical contacts and associations between proteins, often using sequence or structural information and machine learning algorithms.
The statistical and computational analysis of functional annotations assigned to genes using the Gene Ontology framework, often involving enrichment or clustering methods.
Software and web-based tools that enable the construction, simulation, and analysis of metabolic pathways and networks, often using constraint-based modeling approaches.
Software and web-based tools that facilitate the construction, validation, and application of pharmacophore models for virtual screening and drug discovery.
The computational prediction of how a protein adopts its functional three-dimensional structure based on its amino acid sequence and physical interactions.
The statistical and computational analysis of gene expression data, often involving normalization, differential expression analysis, clustering, or pathway enrichment.
The process of inferring the evolutionary relationships among a group of organisms based on genetic data, often involving multiple sequence alignment and tree-building algorithms.
Online repositories of experimentally determined or predicted protein-protein interactions, providing valuable resources for studying protein functions and networks.
A statistical method to determine whether a predefined set of genes shows statistically significant enrichment or depletion of functional annotations compared to a background set.
The computational modeling and simulation of metabolic pathways and networks to predict cellular behavior and phenotypes under different conditions or genetic perturbations.