"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 science of collecting, processing, and analyzing complex biological data using computers.
Molecular Biology: Study of macromolecules and their interactions in biological systems.
Genetics: Study of genes, heredity, and genetic variations that occur in living organisms.
Database Management Systems: The use of software to organize, store, manage and retrieve data efficiently and effectively.
Algorithms and Data Structures: The theoretical and practical study of data organization, storage, and retrieval techniques, and the computation of algorithms used in bioinformatics.
Programming Languages: The study of languages used to write software for bioinformatics (e.g., Python, Perl, R, etc.).
Statistics and Probability: The study of mathematical and computational tools used to analyze and interpret biological data, and the estimation of the probability of research outcomes or their occurrence.
Machine Learning and Artificial Intelligence: The study of algorithms, statistical models, and computational systems that enable computers to learn from and improve with experience and perform tasks that require human-like intelligence.
Structural Bioinformatics: The study of protein and RNA structure, their interactions, and the relationship between structure and function.
Sequence Analysis: The analysis of DNA, RNA and protein sequences to infer biological function, evolutionary relationships, and the prediction of gene structure and function.
Network Analysis and Systems Biology: The study of biological networks at different levels of organization, including molecular, cellular, and organismal, and the exploration of the properties of these networks and their implications for biological function.
Visualization and Communication of Biological Data: The study of methods for effective display and interpretation of complex biological data, such as molecular graphics, interactive visualizations, and data dashboards.
Ethics, Policy and Intellectual Property in Bioinformatics: The study of ethical, legal, and social issues raised by the use of bioinformatics in research and clinical practice, including privacy, access, and data-sharing policies, and intellectual property rights.
"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."