"Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships."
Understanding the basic concepts of biology such as genetics, molecular biology, biochemistry, and cellular biology is crucial for computational biology.
Biological Systems: This topic covers the hierarchy of biological systems, starting from molecules and cells, through tissues, organs and organ systems, and finally, to organisms, populations and ecosystems. Understanding how each component of the hierarchy interacts with others is fundamental to the study of computational biology.
Genomics: This is the study of an organism's complete genetic material or genome, which is made up of DNA. Genomics aims to understand the structure, function, evolution, and expression of genomes.
Proteomics: This is the study of proteins, which carry out many of the functions of cells. Proteomics aims to identify, characterize, and quantify the entire set of proteins in a cell, tissue or organism.
Transcriptomics: This is the study of the transcriptome, which is the complete set of RNA molecules that are produced by a cell, tissue or organism. Transcriptomics aims to identify, quantify and characterize the transcripts in different conditions, in order to understand gene expression patterns.
Metabolomics: This is the study of the metabolome, which is the complete set of small molecule metabolites in a cell, tissue, or organism. Metabolomics aims to understand the biological functions of these metabolites and how they change in response to environmental or genetic factors.
Evolutionary Biology: This is the study of the mechanisms, patterns and consequences of evolution, which is the process by which species change over time. Computational biology is used to analyze and make predictions about the rate, timing, and outcomes of evolutionary events.
Bioinformatics: This is the application of computational methods and tools to analyze biological data, such as DNA sequences, protein structures, and gene expression profiles. Bioinformatics is used to predict the function of genes, identify new drug targets, and understand genetic diseases.
Systems Biology: This is the study of how biological systems and processes work at a molecular, cellular, and organismal level, including the interactions between different components. Computational models are used to simulate and predict the behavior of complex biological systems.
Developmental Biology: This is the study of how an organism develops from a single cell to a complex organism, including the regulation of gene expression and the role of signaling pathways. Computational biology is used to model the complex pathways involved in development.
Biostatistics: This is the application of statistical methods to analyze biological data and make inferences about biological systems. Biostatistics is used to interpret results from experiments, identify patterns in large datasets, and make predictions based on probability models.
Genomics: It involves the study of the DNA sequence and structure of organisms.
Proteomics: It refers to the large-scale study of proteins in an organism and their functions.
Transcriptomics: It is the study of gene expression by measuring RNA transcripts, including mRNA and non-coding RNAs.
Metabolomics: It focuses on the study of small molecule metabolites in biological systems, including identification, quantification, and analysis of metabolites in different biological specimens.
Systems Biology: It is an interdisciplinary field of study that uses computational tools and methods to analyze complex biological systems, including the integration of data from different omics sciences.
Structural Biology: It involves the study of the three-dimensional structure of biomolecules, including DNA, RNA, proteins, and lipids, using computational techniques.
Evolutionary Biology: It uses computational methods and models to study the evolution of different species across time, including their genetics, adaptability, and ecological relationships.
Population Genetics: It is the study of how genetic variations occur and evolve within a population of organisms using computational models.
Cell biology: It involves the study of the structure, function, and behavior of cells, including cellular processes, communication, and signaling.
Bioinformatics: It combines biological data with sophisticated computational methods for analyzing and interpreting the results.
Computational Neuroscience: It uses computational models and algorithms to study the structure and function of the nervous system, including neural networks, brain simulations, and cognitive processes.
Environmental Biology: It focuses on using computational tools and modeling to study the interactions between living organisms and the physical environment, including climate change, habitat loss, and ecosystem services.
Biophysics: It applies physical principles and methods to study biological systems, including simulation of molecular interactions, protein folding, and protein-protein interactions.
Synthetic biology: It involves applying computational tools and methods to design and construct new biological systems with specific functions, including gene circuits, metabolic pathways, and biosensors.
Immunogenetics: It uses computational methods to understand the genetic basis of the immune system, including identification of disease-causing mutations, immune response to pathogens and vaccines, and autoimmunity.
Pharmacogenomics and Personalized medicine: It uses computational tools and predictive models to determine the most effective drug treatments for individual patients based on their genetic makeup and medical history.
Infectious Disease Biology: It involves studying the underlying biology of infectious diseases, including the spread and transmission of pathogens, host-pathogen interactions, and drug resistance.
Biotechnology and Agricultural Science: It involves applying computational methods to improve crop yield, animal breeding, and the production of recombinant proteins and drugs.
Evolutionary Game Theory: It uses mathematical and computational models to understand how different individuals, genes, and species compete and cooperate with each other in the evolutionary process.
Computational Chemistry: It employs computational methods to study the structure, bonding, and reactivity of molecules involved in biological systems, including drug design and development.
"An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics."
"It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers."
"The use of data analysis, mathematical modeling, and computational simulations."
"To understand biological systems and relationships."
"An intersection of computer science, biology, and big data."
"Foundations in applied mathematics, chemistry, and genetics."
"Biological systems and relationships."
"The use of data analysis, mathematical modeling, and computational simulations."
"To build computers."
"An intersection of computer science, biology, and big data."
"Biological systems and relationships."
"Applied mathematics, chemistry, and genetics."
"Mathematical modeling and computational simulations."
"To understand biological systems and relationships."
"An intersection of computer science, biology, and big data."
"It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers."
"The use of data analysis, mathematical modeling, and computational simulations."
"To understand biological systems and relationships."
"Applied mathematics, chemistry, and genetics."