released the predicted structures for hundreds of millions of proteins. one example of this is hemoglobin in humans and the hemoglobin in legumes (leghemoglobin), which are distant relatives from the same protein superfamily. both serve the same purpose of transporting oxygen in the organism. although both of these proteins have completely different amino acid sequences, their protein structures are virtually identical, which reflects their near identical purposes and shared ancestor. other techniques for predicting protein structure include protein threading and de novo (from scratch) physics-based modeling. another aspect of structural bioinformatics include the use of protein structures for virtual screening models such as quantitative structure-activity relationship models and proteochemometric models (pcm). furthermore, a protein's crystal structure can be used in simulation of for example ligand-binding studies and in silico mutagenesis studies. network and systems biology main articles: computational systems biology, biological network, and interactome network analysis seeks to understand the relationships within biological networks such as metabolic or protein–protein interaction networks. although biological networks can be constructed from a single type of molecule or entity (such as genes), network biology often attempts to integrate many different data types, such as proteins, small molecules, gene expression data, and others, which are all connected physically, functionally, or both. systems biology involves the use of computer simulations of cellular subsystems (such as the networks of metabolites and enzymes that comprise metabolism, signal transduction pathways and gene regulatory networks) to both analyze and visualize the complex connections of these cellular processes. artificial life or virtual evolution attempts to understand evolutionary processes via the computer simulation of simple (artificial) life forms. molecular interaction networks interactions between proteins are frequently visualized and analyzed using networks. this network is made up of protein–protein interactions from treponema pallidum, the causative agent of syphilis and other diseases. tens of thousands of three-dimensional protein structures have been determined by x-ray crystallography and protein nuclear magnetic resonance spectroscopy (protein nmr) and a central question in structural bioinformatics is whether it is practical to predict possible protein–protein interactions only based on these 3d shapes, without performing protein–protein interaction experiments. a variety of methods have been developed to tackle the protein–protein docking problem, though it seems that there is still much work to be done in this field. other interactions encountered in the field include protein–ligand (including drug) and protein–peptide. molecular dynamic simulation of movement of atoms about rotatable bonds is the fundamental principle behind computational algorithms, termed docking algorithms, for studying molecular interactions. others literature analysis the growth in the number of published literature makes it virtually impossible to read every paper, resulting in disjointed sub-fields of research. literature analysis aims to employ computational and statistical linguistics to mine this growing library of text resources. for example: abbreviation recognition – identify the long-form and abbreviation of biological terms named-entity recognition – recognizing biological terms such as gene names protein–protein interaction – identify which proteins interact with which proteins from text the area of research draws from statistics and computational linguistics. high-throughput image analysis computational technologies are used to accelerate or fully automate the processing, quantification and analysis of large amounts of high-information-content biomedical imagery. modern image analysis systems augment an observer's ability to make measurements from a large or complex set of images, by improving accuracy, objectivity, or speed. a fully developed analysis system may completely replace the observer. although these systems are not unique to biomedical imagery, biomedical imaging is becoming more important for both diagnostics and research. some examples are: high-throughput and high-fidelity quantification and sub-cellular localization (high-content screening, cytohistopathology, bioimage informatics) morphometrics clinical image analysis and visualization determining the real-time air-flow patterns in breathing lungs of living animals quantifying occlusion size in real-time imagery from the development of and recovery during arterial injury making behavioral observations from extended video recordings of laboratory animals infrared measurements for metabolic activity determination inferring clone overlaps in dna mapping, e.g. the sulston score high-throughput single cell data analysis computational techniques are used to analyse high-throughput, low-measurement single cell data, such as that obtained from flow cytometry. these methods typically involve finding populations of cells that are relevant to a particular disease state or experimental condition. biodiversity informatics biodiversity informatics deals with the collection and analysis of biodiversity data, such as taxonomic databases, or microbiome data. examples of such analyses include phylogenetics, niche modelling, species richness mapping, dna barcoding, or species identification tools. ontologies and data integration biological ontologies are directed acyclic graphs of controlled vocabularies. they are designed to capture biological concepts and descriptions in a way that can be easily categorised and analysed with computers. when categorised in this way, it is possible to gain added value from holistic and integrated analysis. the obo foundry was an effort to standardise certain ontologies. one of the most widespread is the gene ontology which describes gene function. there are also ontologies which describe phenotypes. databases databases are essential for bioinformatics research and applications. many databases exist, covering various information types: for example, dna and protein sequences, molecular structures, phenotypes and biodiversity. databases may contain empirical data (obtained directly from experiments), predicted data (obtained from analysis), or, most commonly, both. they may be specific to a particular organism, pathway or molecule of interest. alternatively, they can incorporate data compiled from multiple other databases. these databases vary in their format, access mechanism, and whether they are public or not. some of the most commonly used databases are listed below. for a more comprehensive list, please check the link at the beginning of the subsection. used in biological sequence analysis: genbank, uniprot used in structure analysis: protein data bank (pdb) used in finding protein families and motif finding: interpro, pfam used for next generation sequencing: sequence read archive used in network analysis: metabolic pathway databases (kegg, biocyc), interaction analysis databases, functional networks used in design of synthetic genetic circuits: genocad software and tools software tools for bioinformatics range from simple command-line tools, to more complex graphical programs and standalone web-services available from various bioinformatics companies or public institutions. open-source bioinformatics software many free and open-source software tools have existed and continued to grow since the 1980s. the combination of a continued need for new algorithms for the analysis of emerging types of biological readouts, the potential for innovative in silico experiments, and freely available open code bases have helped to create opportunities for all research groups to contribute to both bioinformatics and the range of open-source software available, regardless of their funding arrangements. the open source tools often act as incubators of ideas, or community-supported plug-ins in commercial applications. they may also provide de facto standards and shared object models for assisting with the challenge of bioinformation integration. the range of open-source software packages includes titles such as bioconductor, bioperl, biopython, biojava, biojs, bioruby, bioclipse, emboss, .net bio, orange with its bioinformatics add-on, apache taverna, ugene and genocad. to maintain this tradition and create further opportunities, the non-profit open bioinformatics foundation have supported the annual bioinformatics open source conference (bosc) since 2000. web services in bioinformatics soap- and rest-based interfaces have been developed for a wide variety of bioinformatics applications allowing an application running on one computer in one part of the world to use algorithms, data and computing resources on servers in other parts of the world. the main advantages derive from the fact that end users do not have to deal with software and database maintenance overheads. basic bioinformatics services are classified by the ebi into three categories: sss (sequence search services), msa (multiple sequence alignment), and bsa (biological sequence analysis). the availability of these service-oriented bioinformatics resources demonstrate the applicability of web-based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single, standalone or web-based interface, to integrative, distributed and extensible bioinformatics workflow management systems. bioinformatics workflow management systems a bioinformatics workflow management system is a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, in a bioinformatics application. such systems are designed to provide an easy-to-use environment for individual application scientists themselves to create their own workflows, provide interactive tools for the scientists enabling them to execute their workflows and view their results in real-time, simplify the process of sharing and reusing workflows between the scientists, and enable scientists to track the provenance of the workflow execution results and the workflow creation steps. some of the platforms giving this service: galaxy, kepler, taverna, ugene, anduril, hive. biocompute and biocompute objects in 2014, the us food and drug administration sponsored a conference held at the national institutes of health bethesda campus to discuss reproducibility in bioinformatics. over the next three years, a consortium of stakeholders met regularly to discuss what would become biocompute paradigm. these stakeholders included representatives from government, industry, and academic entities. session leaders represented numerous branches of the fda and nih institutes and centers, non-profit entities including the human variome project and the european federation for medical informatics, and research institutions including stanford, the new york genome center, and the george washington university. it was decided that the biocompute paradigm would be in the form of digital 'lab notebooks' which allow for the reproducibility, replication, review, and reuse, of bioinformatics protocols. this was proposed to enable greater continuity within a research group over the course of normal personnel flux while furthering the exchange of ideas between groups. the us fda funded this work so that information on pipelines would be more transparent and accessible to their regulatory staff. in 2016, the group reconvened at the nih in bethesda and discussed the potential for a biocompute object, an instance of the biocompute paradigm. this work was copied as both a "standard trial use" document and a preprint paper uploaded to biorxiv. the biocompute object allows for the json-ized record to be shared among employees, collaborators, and regulators. education platforms as well as in-person masters degree courses being taught at many universities, the computational nature of bioinformatics lends it to computer-aided and online learning. software platforms designed to teach bioinformatics concepts and methods include rosalind and online courses offered through the swiss institute of bioinformatics training portal. the canadian bioinformatics workshops provides videos and slides from training workshops on their website under a creative commons license. the 4273π project or 4273pi project also offers open source educational materials for free. the course runs on low cost raspberry pi computers and has been used to teach adults and school pupils. 4273π is actively developed by a consortium of academics and research staff who have run research level bioinformatics using raspberry pi computers and the 4273π operating system. mooc platforms also provide online certifications in bioinformatics and related disciplines, including coursera's bioinformatics specialization (uc san diego) and genomic data science specialization (johns hopkins) as well as edx's data analysis for life sciences xseries (harvard). conferences there are several large conferences that are concerned with bioinformatics. some of the most notable examples are intelligent systems for molecular biology (ismb), european conference on computational biology (eccb), and research in computational molecular biology (recomb).