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In computational biology, gene prediction or gene finding refers to the process of identifying the regions of genomic DNA that encode genes. This includes protein-coding genes as well as RNA genes, but may also include prediction of other functional elements such as regulatory regions. Gene finding is one of the first and most important steps in understanding the genome of a species once it has been sequenced.
In electrical engineering, statistical computing and bioinformatics, the Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm to compute the statistics for the expectation step.
Comparative genomics is a field of biological research in which the genomic features of different organisms are compared. The genomic features may include the DNA sequence, genes, gene order, regulatory sequences, and other genomic structural landmarks. In this branch of genomics, whole or large parts of genomes resulting from genome projects are compared to study basic biological similarities and differences as well as evolutionary relationships between organisms. The major principle of comparative genomics is that common features of two organisms will often be encoded within the DNA that is evolutionarily conserved between them. Therefore, comparative genomic approaches start with making some form of alignment of genome sequences and looking for orthologous sequences in the aligned genomes and checking to what extent those sequences are conserved. Based on these, genome and molecular evolution are inferred and this may in turn be put in the context of, for example, phenotypic evolution or population genetics.
In bioinformatics, GLIMMER (Gene Locator and Interpolated Markov ModelER) is used to find genes in prokaryotic DNA. "It is effective at finding genes in bacteria, archea, viruses, typically finding 98-99% of all relatively long protein coding genes". GLIMMER was the first system that used the interpolated Markov model to identify coding regions. The GLIMMER software is open source and is maintained by Steven Salzberg, Art Delcher, and their colleagues at the Center for Computational Biology at Johns Hopkins University. The original GLIMMER algorithms and software were designed by Art Delcher, Simon Kasif and Steven Salzberg and applied to bacterial genome annotation in collaboration with Owen White.
Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. The most recent version, Pfam 36.0, was released in September 2023 and contains 20,795 families.
InterPro is a database of protein families, protein domains and functional sites in which identifiable features found in known proteins can be applied to new protein sequences in order to functionally characterise them.
A maximal unique match or MUM, for short, is part of a key step in the multiple sequence alignment of genomes in computational biology. Identification of MUMs and other potential anchors is the first step in larger alignment systems such as MUMmer. Anchors are the areas between two genomes where they are highly similar. To understand what a MUM is we each word in the acronym can be broken down individually. Match implies that the substring occurs in both sequences to be aligned. Unique means that the substring occurs only once in each sequence. Finally, maximal states that the substring is not part of another larger string that fulfills both prior requirements. The idea behind this is that long sequences that match exactly and occur only once in each genome are almost certainly part of the global alignment.
Steven Lloyd Salzberg is an American computational biologist and computer scientist who is a Bloomberg Distinguished Professor of Biomedical Engineering, Computer Science, and Biostatistics at Johns Hopkins University, where he is also Director of the Center for Computational Biology.
Rfam is a database containing information about non-coding RNA (ncRNA) families and other structured RNA elements. It is an annotated, open access database originally developed at the Wellcome Trust Sanger Institute in collaboration with Janelia Farm, and currently hosted at the European Bioinformatics Institute. Rfam is designed to be similar to the Pfam database for annotating protein families.
MUMmer is a bioinformatics software system for sequence alignment. It is based on the suffix tree data structure. It has been used for comparing different genomes assemblies to one another, which allows scientists to determine how a genome has changed. The acronym "MUMmer" comes from "Maximal Unique Matches", or MUMs.
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Anders Krogh is a bioinformatician at the University of Copenhagen, where he leads the university's bioinformatics center. He is known for his pioneering work on the use of hidden Markov models in bioinformatics, and is co-author of a widely used textbook in bioinformatics. In addition, he also co-authored one of the early textbooks on neural networks. His current research interests include promoter analysis, non-coding RNA, gene prediction and protein structure prediction.
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Richard Michael Durbin is a British computational biologist and Al-Kindi Professor of Genetics at the University of Cambridge. He also serves as an associate faculty member at the Wellcome Sanger Institute where he was previously a senior group leader.
In molecular biology and genetics, DNA annotation or genome annotation is the process of describing the structure and function of the components of a genome, by analyzing and interpreting them in order to extract their biological significance and understand the biological processes in which they participate. Among other things, it identifies the locations of genes and all the coding regions in a genome and determines what those genes do.
Sean Roberts Eddy is Professor of Molecular & Cellular Biology and of Applied Mathematics at Harvard University. Previously he was based at the Janelia Research Campus from 2006 to 2015 in Virginia. His research interests are in bioinformatics, computational biology and biological sequence analysis. As of 2016 projects include the use of Hidden Markov models in HMMER, Infernal Pfam and Rfam.
TIGRFAMs is a database of protein families designed to support manual and automated genome annotation. Each entry includes a multiple sequence alignment and hidden Markov model (HMM) built from the alignment. Sequences that score above the defined cutoffs of a given TIGRFAMs HMM are assigned to that protein family and may be assigned the corresponding annotations. Most models describe protein families found in Bacteria and Archaea.
A context model defines how context data are structured and maintained. It aims to produce a formal or semi-formal description of the context information that is present in a context-aware system. In other words, the context is the surrounding element for the system, and a model provides the mathematical interface and a behavioral description of the surrounding environment.
SEA-PHAGES stands for Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science; it was formerly called the National Genomics Research Initiative. This was the first initiative launched by the Howard Hughes Medical Institute (HHMI) Science Education Alliance (SEA) by their director Tuajuanda C. Jordan in 2008 to improve the retention of Science, technology, engineering, and mathematics (STEM) students. SEA-PHAGES is a two-semester undergraduate research program administered by the University of Pittsburgh's Graham Hatfull's group and the Howard Hughes Medical Institute's Science Education Division. Students from over 100 universities nationwide engage in authentic individual research that includes a wet-bench laboratory and a bioinformatics component.
References
- ↑ "UM School of Medicine's Institute for Genome Sciences Awarded $17.5 Million Grant for Infectious Disease Research". University of Maryland School of Medicine. April 4, 2019. Retrieved 14 June 2023.
- ↑ Owen White publications indexed by Google Scholar
- ↑ Owen White at DBLP Bibliography Server
- 1 2 3 "University of Maryland School of Medicine". news.medschool.umaryland.edu. Retrieved 15 September 2017.
- ↑ "Recent Graduates | Molecular Biology". molb.research.nmsu.edu. Retrieved 15 September 2017.
- ↑ Salzberg, SL; Delcher, AL; Kasif, S; White, O (15 January 1998). "Microbial gene identification using interpolated Markov models". Nucleic Acids Research. 26 (2): 544–8. doi:10.1093/nar/26.2.544. PMC 147303 . PMID 9421513.
- ↑ Delcher, AL; Harmon, D; Kasif, S; White, O; Salzberg, SL (1 December 1999). "Improved microbial gene identification with GLIMMER". Nucleic Acids Research. 27 (23): 4636–41. doi:10.1093/nar/27.23.4636. PMC 148753 . PMID 10556321.
- ↑ Pevsner, Jonathan (2015). Bioinformatics and Functional Genomics (3rd ed.). John Wiley & Sons. p. 821. ISBN 9781118581766.
- ↑ Delcher, A. L.; Kasif, S.; Fleischmann, R. D.; Peterson, J.; White, O.; Salzberg, S. L. (1 January 1999). "Alignment of whole genomes". Nucleic Acids Research. 27 (11): 2369–2376. doi:10.1093/nar/27.11.2369. PMC 148804 . PMID 10325427.
- ↑ "White, Owen | University of Maryland School of Medicine". www.medschool.umaryland.edu. Retrieved 15 September 2017.
- 1 2 "Benjamin Franklin Award - Bioinformatics.org". www.bioinformatics.org. Retrieved 15 September 2017.
- ↑ "Owen White Receives 2015 Benjamin Franklin Award at Bio-IT World Conference". www.bio-itworld.com. Retrieved 15 September 2017.
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