Sean Eddy

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Sean Eddy
Sean-eddy.jpg
Sean Eddy
Born
Sean Roberts Eddy
Alma mater
Known for
Awards Ben Franklin award (2007)
Scientific career
Fields Computational Genome Analysis [5]
Institutions
Thesis Introns in the T-even bacteriophages  (1991)
Doctoral advisor Larry Gold [6]
Other academic advisors John Sulston
Richard Durbin
Website

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 [5] [7] [8] in Virginia. His research interests are in bioinformatics, computational biology and biological sequence analysis. [9] [10] [11] [12] As of 2016 projects include the use of Hidden Markov models [13] [14] in HMMER, Infernal [15] Pfam and Rfam. [16] [17] [18] [19]

Contents

Education

Eddy graduated June, 1982 from Marion Center Area High School, Marion Center, Pennsylvania. He then completed a Bachelor of Science in Biology at California Institute of Technology in 1986, [20] followed by a Doctor of Philosophy in molecular biology at the University of Colorado under the supervision of Larry Gold in 1991 studying the T4 phage. [6] [21] [22]

Career

From 1992 to 1995 he was a postdoctoral research fellow at the Medical Research Council (MRC) Laboratory of Molecular Biology (LMB) in Cambridge UK working with John Sulston and Richard Durbin. From 1995 to 2007 he worked at Washington University School of Medicine and has been working for the Howard Hughes Medical Institute since 2000.

Awards and honours

In 2007, Sean was the winner of the Benjamin Franklin Award in Bioinformatics for contributions to Open Access in the Life Sciences. [23]

In 2022, Eddy was elected as a Fellow of the International Society for Computational Biology. [24]

Related Research Articles

<span class="mw-page-title-main">Pfam</span> Database of protein families

Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. The latest version of Pfam, 37.0, was released in June 2024 and contains 21,979 families. It is currently provided through InterPro website.

<span class="mw-page-title-main">Ewan Birney</span> English businessman

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.

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.

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.

<span class="mw-page-title-main">HMMER</span> Software package for sequence analysis

HMMER is a free and commonly used software package for sequence analysis written by Sean Eddy. Its general usage is to identify homologous protein or nucleotide sequences, and to perform sequence alignments. It detects homology by comparing a profile-HMM to either a single sequence or a database of sequences. Sequences that score significantly better to the profile-HMM compared to a null model are considered to be homologous to the sequences that were used to construct the profile-HMM. Profile-HMMs are constructed from a multiple sequence alignment in the HMMER package using the hmmbuild program. The profile-HMM implementation used in the HMMER software was based on the work of Krogh and colleagues. HMMER is a console utility ported to every major operating system, including different versions of Linux, Windows, and macOS.

SUPERFAMILY is a database and search platform of structural and functional annotation for all proteins and genomes. It classifies amino acid sequences into known structural domains, especially into SCOP superfamilies. Domains are functional, structural, and evolutionary units that form proteins. Domains of common Ancestry are grouped into superfamilies. The domains and domain superfamilies are defined and described in SCOP. Superfamilies are groups of proteins which have structural evidence to support a common evolutionary ancestor but may not have detectable sequence homology.

<span class="mw-page-title-main">Richard M. Durbin</span> British computational biologist

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.

<span class="mw-page-title-main">Lincoln Stein</span> American scientist and academic

Lincoln David Stein is a scientist and Professor in bioinformatics and computational biology at the Ontario Institute for Cancer Research.

<span class="mw-page-title-main">Cyrus Chothia</span> English biochemist (1942–2019)

Cyrus Homi Chothia was an English biochemist who was an emeritus scientist at the Medical Research Council (MRC) Laboratory of Molecular Biology (LMB) at the University of Cambridge and emeritus fellow of Wolfson College, Cambridge.

Cancer systems biology encompasses the application of systems biology approaches to cancer research, in order to study the disease as a complex adaptive system with emerging properties at multiple biological scales. Cancer systems biology represents the application of systems biology approaches to the analysis of how the intracellular networks of normal cells are perturbed during carcinogenesis to develop effective predictive models that can assist scientists and clinicians in the validations of new therapies and drugs. Tumours are characterized by genomic and epigenetic instability that alters the functions of many different molecules and networks in a single cell as well as altering the interactions with the local environment. Cancer systems biology approaches, therefore, are based on the use of computational and mathematical methods to decipher the complexity in tumorigenesis as well as cancer heterogeneity.

<span class="mw-page-title-main">Alex Bateman</span> British bioinformatician

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.

Julian John Thurstan Gough was a Group Leader in the Laboratory of Molecular Biology (LMB) of the Medical Research Council (MRC). He was previously a professor of bioinformatics at the University of Bristol.

<span class="mw-page-title-main">Christine Orengo</span> Professor of Bioinformatics

Christine Anne Orengo is a Professor of Bioinformatics at University College London (UCL) known for her work on protein structure, particularly the CATH database. Orengo serves as president of the International Society for Computational Biology (ISCB), the first woman to do so in the history of the society.

Non-coding RNAs have been discovered using both experimental and bioinformatic approaches. Bioinformatic approaches can be divided into three main categories. The first involves homology search, although these techniques are by definition unable to find new classes of ncRNAs. The second category includes algorithms designed to discover specific types of ncRNAs that have similar properties. Finally, some discovery methods are based on very general properties of RNA, and are thus able to discover entirely new kinds of ncRNAs.

DIMPL is a bioinformatic pipeline that enables the extraction and selection of bacterial GC-rich intergenic regions (IGRs) that are enriched for structured non-coding RNAs (ncRNAs). The method of enriching bacterial IGRs for ncRNA motif discovery was first reported for a study in "Genome-wide discovery of structured noncoding RNAs in bacteria".

References

  1. ↑ Finn, R. D.; Clements, J.; Eddy, S. R. (2011). "HMMER web server: Interactive sequence similarity searching". Nucleic Acids Research. 39 (Web Server issue): W29–W37. doi:10.1093/nar/gkr367. PMC   3125773 . PMID   21593126.
  2. ↑ Nawrocki, E. P.; Kolbe, D. L.; Eddy, S. R. (2009). "Infernal 1.0: Inference of RNA alignments". Bioinformatics . 25 (10): 1335–1337. doi:10.1093/bioinformatics/btp157. PMC   2732312 . PMID   19307242.
  3. ↑ Bateman, A.; Coin, L.; Durbin, R.; Finn, R. D.; Hollich, V.; Griffiths-Jones, S.; Khanna, A.; Marshall, M.; Moxon, S.; Sonnhammer, E. L.; Studholme, D. J.; Yeats, C.; Eddy, S. R. (2004). "The Pfam protein families database". Nucleic Acids Research . 32 (Database issue): 138D–1141. doi:10.1093/nar/gkh121. ISSN   0305-1048. PMC   308855 . PMID   14681378. Open Access logo PLoS transparent.svg
  4. ↑ Gardner, P. P.; Daub, J.; Tate, J.; Moore, B. L.; Osuch, I. H.; Griffiths-Jones, S.; Finn, R. D.; Nawrocki, E. P.; Kolbe, D. L.; Eddy, S. R.; Bateman, A. (2010). "Rfam: Wikipedia, clans and the "decimal" release". Nucleic Acids Research . 39 (Database issue): D141–D145. doi:10.1093/nar/gkq1129. PMC   3013711 . PMID   21062808.
  5. 1 2 Sean Eddy publications indexed by Google Scholar
  6. 1 2 Eddy, Sean Roberts (1991). Introns in the T-even bacteriophages (PhD thesis). University of Colorado. OCLC   28253022. ProQuest   303935681.
  7. ↑ Anon (2012). "HHMI Scientist Bio: Sean R. Eddy, Ph.D." Archived from the original on 2012-06-16.
  8. ↑ Kaplan, Karen (2011). "A roll of the dice: Sean Eddy has his dream job". Nature . 479 (7373): 433–435. doi: 10.1038/nj7373-433a . PMID   22106470.
  9. ↑ Durbin, Richard M.; Eddy, Sean R.; Krogh, Anders; Mitchison, Graeme (1998), Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids (1st ed.), Cambridge, New York: Cambridge University Press, ISBN   0-521-62971-3, OCLC   593254083
  10. ↑ Rivas, E.; Lang, R.; Eddy, S. R. (2011). "A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more". RNA. 18 (2): 193–212. doi:10.1261/rna.030049.111. PMC   3264907 . PMID   22194308.
  11. ↑ Lander, E. S.; Linton, M.; Birren, B.; Nusbaum, C.; Zody, C.; Baldwin, J.; Devon, K.; Dewar, K.; Doyle, M.; Fitzhugh, W.; Funke, R.; Gage, D.; Harris, K.; Heaford, A.; Howland, J.; Kann, L.; Lehoczky, J.; Levine, R.; McEwan, P.; McKernan, K.; Meldrim, J.; Mesirov, J. P.; Miranda, C.; Morris, W.; Naylor, J.; Raymond, C.; Rosetti, M.; Santos, R.; Sheridan, A.; et al. (Feb 2001). "Initial sequencing and analysis of the human genome" (PDF). Nature. 409 (6822): 860–921. Bibcode:2001Natur.409..860L. doi: 10.1038/35057062 . ISSN   0028-0836. PMID   11237011.
  12. ↑ "Sean Eddy's homepage". selab.janelia.org. Archived from the original on 2010-12-04.
  13. ↑ Eddy, S. R. (2004). "What is a hidden Markov model?". Nature Biotechnology . 22 (10): 1315–1316. doi: 10.1038/nbt1004-1315 . PMID   15470472.
  14. ↑ Eddy, S. (1998). "Profile hidden Markov models". Bioinformatics. 14 (9): 755–763. doi: 10.1093/bioinformatics/14.9.755 . PMID   9918945.
  15. ↑ "Sean Eddy's blog". cryptogenomicon.org.
  16. ↑ Eddy, S. R. (2012). "The C-value paradox, junk DNA and ENCODE". Current Biology. 22 (21): R898–R899. doi: 10.1016/j.cub.2012.10.002 . PMID   23137679.
  17. ↑ Sean Eddy's publications indexed by the Scopus bibliographic database. (subscription required)
  18. ↑ Reading Genomes Bit by Bit - Sean Eddy on YouTube, GenomeTV
  19. ↑ Sean Eddy Keynote OBF BOSC on YouTube, 2013-07-20
  20. ↑ "Sean Eddy CV" (PDF). selab.janelia.org. Archived from the original (PDF) on 2012-03-09.
  21. ↑ Eddy, S. R.; Gold, L. (1991). "The phage T4 nrdB intron: A deletion mutant of a version found in the wild". Genes & Development. 5 (6): 1032–1041. doi: 10.1101/gad.5.6.1032 . PMID   2044951.
  22. ↑ Tuerk, C.; Eddy, S.; Parma, D.; Gold, L. (1990). "Autogenous translational operator recognized by bacteriophage T4 DNA polymerase". Journal of Molecular Biology . 213 (4): 749–761. doi:10.1016/S0022-2836(05)80261-X. PMID   2359122.
  23. ↑ Anon (2007). "BioMed Central Blog: Sean Eddy wins open access award". blogs.openaccesscentral.com. Archived from the original on 2011-06-07.
  24. ↑ "April 28, 2022: ISCB Congratulates and Introduces the 2022 Class of Fellows!". www.iscb.org. Retrieved 17 June 2022.
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