In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix. Gaps are inserted between the residues so that identical or similar characters are aligned in successive columns. Sequence alignments are also used for non-biological sequences, such as calculating the distance cost between strings in a natural language or in financial data.
The Protein Information Resource (PIR), located at Georgetown University Medical Center, is an integrated public bioinformatics resource to support genomic and proteomic research, and scientific studies. It contains protein sequences databases
Clustal is a series of widely used computer programs used in bioinformatics for multiple sequence alignment. There have been many versions of Clustal over the development of the algorithm that are listed below. The analysis of each tool and its algorithm is also detailed in their respective categories. Available operating systems listed in the sidebar are a combination of the software availability and may not be supported for every current version of the Clustal tools. Clustal Omega has the widest variety of operating systems out of all the Clustal tools.
The European Bioinformatics Institute (EMBL-EBI) is an intergovernmental organization (IGO) which, as part of the European Molecular Biology Laboratory (EMBL) family, focuses on research and services in bioinformatics. It is located on the Wellcome Genome Campus in Hinxton near Cambridge, and employs over 600 full-time equivalent (FTE) staff. Institute leaders such as Rolf Apweiler, Alex Bateman, Ewan Birney, and Guy Cochrane, an adviser on the National Genomics Data Center Scientific Advisory Board, serve as part of the international research network of the BIG Data Center at the Beijing Institute of Genomics.
In evolutionary biology, conserved sequences are identical or similar sequences in nucleic acids or proteins across species, or within a genome, or between donor and receptor taxa. Conservation indicates that a sequence has been maintained by natural selection.
Multiple sequence alignment (MSA) may refer to the process or the result of sequence alignment of three or more biological sequences, generally protein, DNA, or RNA. In many cases, the input set of query sequences are assumed to have an evolutionary relationship by which they share a linkage and are descended from a common ancestor. From the resulting MSA, sequence homology can be inferred and phylogenetic analysis can be conducted to assess the sequences' shared evolutionary origins. Visual depictions of the alignment as in the image at right illustrate mutation events such as point mutations that appear as differing characters in a single alignment column, and insertion or deletion mutations that appear as hyphens in one or more of the sequences in the alignment. Multiple sequence alignment is often used to assess sequence conservation of protein domains, tertiary and secondary structures, and even individual amino acids or nucleotides.
John Frederick William Birney is joint director of EMBL's European Bioinformatics Institute (EMBL-EBI), in Hinxton, Cambridgeshire and deputy director general of the European Molecular Biology Laboratory (EMBL). He also serves as non-executive director of Genomics England, chair of the Global Alliance for Genomics and Health (GA4GH) and honorary professor of bioinformatics at the University of Cambridge. Birney has made significant contributions to genomics, through his development of innovative bioinformatics and computational biology tools. He previously served as an associate faculty member at the Wellcome Trust Sanger Institute.
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.
T-Coffee is a multiple sequence alignment software using a progressive approach. It generates a library of pairwise alignments to guide the multiple sequence alignment. It can also combine multiple sequences alignments obtained previously and in the latest versions can use structural information from PDB files (3D-Coffee). It has advanced features to evaluate the quality of the alignments and some capacity for identifying occurrence of motifs (Mocca). It produces alignment in the aln format (Clustal) by default, but can also produce PIR, MSF, and FASTA format. The most common input formats are supported.
David J. Lipman is an American biologist who from 1989 to 2017 was the director of the National Center for Biotechnology Information (NCBI) at the National Institutes of Health. NCBI is the home of GenBank, the U.S. node of the International Sequence Database Consortium, and PubMed, one of the most heavily used sites in the world for the search and retrieval of biomedical information. Lipman is one of the original authors of the BLAST sequence alignment program, and a respected figure in bioinformatics. In 2017, he left NCBI and became Chief Science Officer at Impossible Foods.
MUltiple Sequence Comparison by Log-Expectation (MUSCLE) is computer software for multiple sequence alignment of protein and nucleotide sequences. It is licensed as public domain. The method was published by Robert C. Edgar in two papers in 2004. The first paper, published in Nucleic Acids Research, introduced the sequence alignment algorithm. The second paper, published in BMC Bioinformatics, presented more technical details.
Webb Colby Miller is an American bioinformatician who is professor in the Department of Biology and the Department of Computer Science and Engineering at The Pennsylvania State University.
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.
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.
Rolf Apweiler is a director of European Bioinformatics Institute (EBI) part of the European Molecular Biology Laboratory (EMBL) with Ewan Birney.
Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).
Alexander George Bateman is a computational biologist and Head of Protein Sequence Resources at the European Bioinformatics Institute (EBI), part of the European Molecular Biology Laboratory (EMBL) in Cambridge, UK. He has led the development of the Pfam biological database and introduced the Rfam database of RNA families. He has also been involved in the use of Wikipedia for community-based annotation of biological databases.
Paul Martin Sharp is Professor of Genetics at the University of Edinburgh, where he holds the Alan Robertson chair of genetics in the Institute of Evolutionary Biology.
Toby James Gibson is a group leader and biochemist at the European Molecular Biology Laboratory (EMBL) in Heidelberg known for his work on Clustal. According to Nature, Gibson's co-authored papers describing Clustal are among the top ten most highly cited scientific papers of all time.
