computational biology computational biology involves the development and application of dataanalytical and theoretical methods mathematical modeling and computational simulation techniques to the study of biological ecological behavioral and social systems computational biology is different from biological computing which is a subfield of computer science and computer engineering using bioengineering and biology to build computers but is similar to bioinformatics which is an interdisciplinary science using computers to store and process biological data introduction computational biology which includes many aspects of bioinformatics is the science of using biological data to develop algorithms or models to understand biological systems and relationships until recently biologists did not have access to very large amounts of data this data has now become commonplace particularly in molecular biology and genomics researchers were able to develop analytical methods for interpreting biological information but were unable to share them quickly among colleagues bioinformatics began to develop in the early 1970s it was considered the science of analyzing informatics processes of various biological systems at this time research in artificial intelligence was using network models of the human brain in order to generate new algorithms this use of biological data to develop other fields pushed biological researchers to revisit the idea of using computers to evaluate and compare large data sets by 1982 information was being shared among researchers through the use of punch cards the amount of data being shared began to grow exponentially by the end of the 1980s this required the development of new computational methods in order to quickly analyze and interpret relevant information since the late 1990s computational biology has become an important part of developing emerging technologies for the field of biology the terms computational biology and evolutionary computation have a similar name but are not to be confused unlike computational biology evolutionary computation is not concerned with modeling and analyzing biological data it instead creates algorithms based on the ideas of evolution across species sometimes referred to as genetic algorithms the research of this field can be applied to computational biology while evolutionary computation is not inherently a part of computational biology computational evolutionary biology is a subfield of it computational biology has been used to help sequence the human genome create accurate models of the human brain and assist in modeling biological systems subfields computational anatomy computational anatomy computational anatomy is a discipline focusing on the study of anatomical shape and form at the visible or gross anatomical 50 100 displaystyle 50100mu scale of morphology it involves the development and application of computational mathematical and dataanalytical methods for modeling and simulation of biological structures it focuses on the anatomical structures being imaged rather than the medical imaging devices due to the availability of dense 3d measurements via technologies such as magnetic resonance imaging mri computational anatomy has emerged as a subfield of medical imaging and bioengineering for extracting anatomical coordinate systems at the morphome scale in 3d the original formulation of computational anatomy is as a generative model of shape and form from exemplars acted upon via transformations the diffeomorphism group is used to study different coordinate systems via coordinate transformations as generated via the lagrangian and eulerian velocities of flow from one anatomical configuration in r 3 displaystyle mathbb r 3 to another it relates with shape statistics and morphometrics with the distinction that diffeomorphisms are used to map coordinate systems whose study is known as diffeomorphometry computational biomodeling modelling biological systems computational biomodeling is a field concerned with building computer models of biological systems computational biomodeling aims to develop and use visual simulations in order to assess the complexity of biological systems this is accomplished through the use of specialized algorithms and visualization software these models allow for prediction of how systems will react under different environments this is useful for determining if a system is robust a robust biological system is one that maintain their state and functions against external and internal perturbations a useful modelling approach is to use petri nets via tools such as esyn computational genomics computational genetics a partially sequenced genome computational genomics computational genomics is a field within genomics which studies the genomes of cells and organisms it is sometimes referred to as computational and statistical genetics and encompasses much of bioinformatics the human genome project is one example of computational genomics this project looks to sequence the entire human genome into a set of data once fully implemented this could allow for doctors to analyze the genome of an individual patient one of the main ways that genomes are compared is by sequence homology homology is the study of biological structures and nucleotide sequences in different organisms that come from a common ancestor research suggests that between 80 and 90 of genes in newly sequenced prokaryotic genomes can be identified this way this field is still in development an untouched project in the development of computational genomics is the analysis of intergenic regions studies show that roughly 97 of the human genome consists of these regions researchers in computational genomics are working on understanding the functions of noncoding regions of the human genome through the development of computational and statistical methods and via large consortia projects such as encode the encyclopedia of dna elements and the roadmap epigenomics project computational neuroscience computational neuroscience computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system it is a subset of the field of neuroscience and looks to analyze brain data to create practical applications it looks to model the brain in order to examine specific types aspects of the neurological system various types of models of the brain include realistic brain models these models look to represent every aspect of the brain including as much detail at the cellular level as possible realistic models provide the most information about the brain but also have the largest margin for error more variables in a brain model create the possibility for more error to occur these models do not account for parts of the cellular structure that scientists do not know about realistic brain models are the most computationally heavy and the most expensive to implement simplifying brain models these models look to limit the scope of a model in order to assess a specific physical property of the neurological system this allows for the intensive computational problems to be solved and reduces the amount of potential error from a realistic brain model it is the work of computational neuroscientists to improve the algorithms and data structures currently used to increase the speed of such calculations computational pharmacology computational pharmacology from a computational biology perspective is the study of the effects of genomic data to find links between specific genotypes and diseases and then screening drug data analysts project that if major medications fail due to patents that computational biology will be necessary to replace current drugs on the market doctoral students in computational biology are being encouraged to pursue careers in industry rather than take postdoctoral positions this is a direct result of major pharmaceutical companies needing more qualified analysts of the large data sets required for producing new drugs computational evolutionary biology computational biology has assisted the field of evolutionary biology in many capacities this includes using dna data to reconstruct the tree of life with computational phylogenetics fitting population genetics models either forward time or backward time to dna data to make inferences about demographic or selective history building population genetics models of evolutionary systems from first principles in order to predict what is likely to evolve cancer computational biology cancer computational biology is a field that aims to determine the future mutations in cancer through an algorithmic approach to analyzing data research in this field has led to the use of highthroughput measurement high throughput measurement allows for the gathering of millions of data points using robotics and other sensing devices this data is collected from dna rna and other biological structures areas of focus include determining the characteristics of tumors analyzing molecules that are deterministic in causing cancer and understanding how the human genome relates to the causation of tumors and cancer computational neuropsychiatry computational neuropsychiatry is the emerging field that uses mathematical and computerassisted modeling of brain mechanisms involved in mental disorders it was already demonstrated by several initiatives that computational modeling is an important contribution to understand neuronal circuits that could generate mental functions and dysfunctions software and tools computational biologists use a wide range of software these range from command line programs to graphical and webbased programs open source software open source software provides a platform to develop computational biological methods specifically open source means that every person andor entity can access and benefit from software developed in research plos cites four main reasons for the use of open source software including reproducibility this allows for researchers to use the exact methods used to calculate the relations between biological data faster development developers and researchers do not have to reinvent existing code for minor tasks instead they can use preexisting programs to save time on the development and implementation of larger projects increased quality having input from multiple researchers studying the same topic provides a layer of assurance that errors will not be in the code longterm availability open source programs are not tied to any businesses or patents this allows for them to be posted to multiple web pages and ensure that they are available in the future conferences there are several large conferences that are concerned with computational biology some notable examples are intelligent systems for molecular biology ismb european conference on computational biology eccb and research in computational molecular biology recomb journals there are numerous journals dedicated to computational biology some notable examples include journal of computational biology and plos computational biology the plos computational biology journal is a peerreviewed journal that has many notable research projects in the field of computational biology they provide reviews on software tutorials for open source software and display information on upcoming computational biology conferences plos computational biology is an open access journal the publication may be openly used provided the author is cited recently a new open access journal computational molecular biology was launched related fields computational biology bioinformatics and mathematical biology are all interdisciplinary approaches to the life sciences that draw from quantitative disciplines such as mathematics and information science the nih describes computationalmathematical biology as the use of computationalmathematical approaches to address theoretical and experimental questions in biology and by contrast bioinformatics as the application of information science to understand complex lifesciences data specifically the nih defines computational biology the development and application of dataanalytical and theoretical methods mathematical modeling and computational simulation techniques to the study of biological behavioral and social systems bioinformatics research development or application of computational tools and approaches for expanding the use of biological medical behavioral or health data including those to acquire store organize archive analyze or visualize such data while each field is distinct there may be significant overlap at their interface international society for computational biology list of bioinformatics institutions list of biological databases bioinformatics biosimulation biostatistics computational chemistry computational science computational history biological simulation mathematical biology monte carlo method molecular modeling network biology structural genomics synthetic biology systems biology bioinformaticsorg vtebioinformaticsdatabases sequence databases genbank european nucleotide archive and dna data bank of japan secondary databases uniprot database of protein sequences grouping together swissprot trembl and protein information resource other databases protein data bank ensembl and interpro specialised genomic databases bold saccharomyces genome database flybase vectorbase wormbase phibase arabidopsis information resource and zebrafish information network software blast bowtie clustal hmmer muscle samtools tophat other server expasy ontology gene ontology institutions european bioinformatics institute us national center for biotechnology information swiss institute of bioinformatics japanese institute of genetics philippine genome center broad institute wellcome sanger institute organizations international society for computational biology iscb european molecular biology network embnet african society for bioinformatics and computational biology asbcb japanese society for bioinformatics jsbi meetings intelligent systems for molecular biology ismb research in computational molecular biology recomb european conference on computational biology eccb pacific symposium on biocomputing psb iscb africa asbcb conference on bioinformatics basel computational biology conference international conference on bioinformatics incob related topics computational biology list of biological databases sequencing sequence database sequence alignment molecular phylogenetics category commons portal 