"Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex."
The use of computer science to analyze and interpret biological data.
Molecular Biology: Understanding the structure, function, and interactions of biological molecules such as DNA, RNA, and proteins.
Genetics: Understanding the principles of inheritance and genetic variation at the molecular level.
Genomics: Studying the structure and function of genomes, including sequencing and annotation of genes.
Proteomics: Studying the structure and function of proteins and their interactions within cells.
Computer Science: Understanding the algorithms and programming languages used in bioinformatics, such as Python and R.
Statistics: Understanding the statistical methods used to analyze large datasets in bioinformatics.
Data Analysis: Understanding the tools and techniques used to analyze and visualize large datasets in bioinformatics.
Machine Learning: Understanding the algorithms used to develop predictive models for analyzing biological data.
Systems Biology: Understanding how biological systems function at a molecular level and how they interact with each other.
Comparative Genomics: Comparing and analyzing the genomes of different organisms to understand their relationships and evolutionary history.
Biostatistics: Understanding the statistical methods used for analyzing clinical data and developing clinical trials.
Pharmacogenomics: Understanding how genetic variation influences drug efficacy and toxicity.
Structural Biology: Understanding the structures of biological macromolecules such as proteins and nucleic acids.
Data Visualization: Understanding the tools and techniques used to create visual representations of biological data.
Evolutionary Biology: Understanding the processes that drive the evolution of biological systems.
Synthetic Biology: Designing and engineering biological systems for specific applications.
Epigenetics: Understanding how environmental factors can influence gene expression and cellular function.
Immunology: Understanding the biological processes involved in the immune response and disease.
Biomedical Engineering: Applying engineering principles to develop solutions and technologies for biomedical problems.
Bioethics: Understanding the ethical, legal, and social implications of bioinformatics research and technologies.
Genomics: The study of the complete set of genetic information present in an organism's DNA.
Transcriptomics: The study of gene expression patterns in an organism at a given point in time using RNA-sequencing or microarrays.
Proteomics: The study of the entire set of proteins produced by an organism or a cell type, as well as their interactions and modifications.
Metabolomics: The study of the complete set of small molecules present in a biological system, including metabolites, lipids, and other compounds involved in metabolic processes.
Systems Biology: The study of the complex interactions between all of the components of a biological system, including its genes, proteins, and metabolites.
Computational Biology: The development and application of computational techniques to analyze biological data and mathematical models to explain complex biological phenomena.
Structural Biology: The study of the three-dimensional structure of biological macromolecules, such as proteins and nucleic acids, and how their structures relate to their functions.
Pharmacogenomics: The study of how genetic variation affects an individual's response to drugs and their efficacy and safety.
Biostatistics: The application of statistical methods to biological data sets, including hypothesis testing, experimental design, and data analysis.
Evolutionary Biology: The study of the history of life on Earth, including the mechanisms of evolution and the relationships between different species.
Synthetic Biology: The engineering of biological systems, including the design and construction of novel genetic circuits, metabolic pathways, and other biological components.
Epigenetics: The study of changes in gene expression that are not caused by alterations in the underlying DNA sequence.
Structural Genomics: The study of the 3-D structures of large sets of biological macromolecules.
Immunoinformatics: The study of the structure and function of immune system components and their interactions with antigens.
Environmental Bioinformatics: The study of the effects of environmental factors on biological systems, such as the impact of pollutants on ecosystems and the role of microorganisms in bioremediation.
Functional Genomics: The study of the functional roles of all genes in the genome.
Comparative Genomics: The comparison of the genome sequences of different species to identify commonalities and differences that can provide insights into evolutionary relationships and potential functional roles.
Network Biology: The study of the networks of signaling pathways and metabolic reactions that control cellular processes and interactions between different cells and tissues.
Population Genetics: The study of how genetic variation is distributed within and among populations of organisms, and how it changes over time.
Medical Informatics: The application of computer-based tools and techniques to improve the practice of medicine and healthcare delivery, including electronic medical records, decision support systems, and clinical trials data management systems.
"Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics, and statistics to analyze and interpret biological data."
"The subsequent process of analyzing and interpreting data is referred to as computational biology."
"Computational, statistical, and computer programming techniques have been used for computer simulation analyses of biological queries."
"These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations."
"Proteomics tries to understand the organizational principles within nucleic acid and protein sequences."
"Image and signal processing allow extraction of useful results from large amounts of raw data."
"In the field of genetics, it aids in sequencing and annotating genomes and their observed mutations."
"Bioinformatics includes text mining of biological literature."
"Bioinformatics includes the development of biological and gene ontologies to organize and query biological data."
"It also plays a role in the analysis of gene and protein expression and regulation."
"Bioinformatics tools aid in comparing, analyzing, and interpreting genetic and genomic data."
"Bioinformatics aids in the understanding of evolutionary aspects of molecular biology."
"At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology."
"In structural biology, it aids in the simulation and modeling of DNA, RNA, proteins, as well as biomolecular interactions."