Jaap Heringa

	Professor of Bioinformatics Director, Centre for Integrative Bioinformatics VU Room P1.28 Bioinformatics Section Dept.of Computer Science Faculty of Sciences Vrije Universiteit De Boelelaan  1081A 1081 HV Amsterdam The Netherlands
	email:	heringa@cs.vu.nl
	telephone:	+31 20 59 87649 (direct)
		+31 20 59 83563 (secr.)
fax:	+31 20 59 87653

Academic Education	Work Experience	Research Interests	Editorial Board Memberships	Selected References	Selected Methods
Academic Education 1980: B.Sc. Hons. Mathematical Biology 1984: M.Sc. Biology, Majors Bioinformatics and Population Genetics, Minor Computer Science 1993: Ph.D. Bioinformatics (Cum Laude), University of Utrecht, The Netherlands. Thesis title: Local Interactions in Protein Folds: A Bioinformatic Approach Work Experience 1980 - 1984: Assistant Research Consultant (multivariate statistics), one day per week, University of Utrecht, The Netherlands 1985 - 1988: Development Programmer and Team Leader with IBM Informations Network Service Development Center (INSDC), Uithoorn, The Netherlands 1988 - 1996: Staff Researcher, Biocomputing department, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany 1996 - 2002: Group leader, Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK 2002 - 2003: MRC Senior Scientist, Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK 2002 - Date: Professor of Bioinformatics, Free University, Amsterdam, The Netherlands 2002 - Date: Head of Bioinformatics Section, Faculty of Sciences, Free University, Amsterdam, The Netherlands 2003 - Date: Director of the Centre for Integrative Bioinformatics VU (IBIVU), Free University, Amsterdam, The Netherlands 2009 - Date: Director of the Netherlands Bioinformatics Centre (NBIC) Education Platform "BioWise" 2010 - Date: Scientific Director of the Netherlands Bioinformatics Centre (NBIC) Research Interests Bioinformatics methods and data integration Genome analysis Systems Biology Protein structure prediction Domain boundary prediction Secondary structure prediction Sequence database searching Multiple sequence alignment Multiple sequence alignment and (predicted) secondary or tertiary structure information Multiple sequence alignment and profile analysis using local weighting schemes Multiple sequence alignment parameter optimalisation using genetic algorithms Multiple sequence alignment quality control and iterative optimisation Repeats-aware multiple alignment Genomic and internal protein repeats detection Micro-array (gene expression) analysis in the context of Ecogenomics Editorial Board Memberships Applied Bioinformatics Bioinformatics Computational Biology and Chemistry (CBAC) Current Peptide and Protein Research (CPPS) Evolutionary Bioinformatics Selected References Heringa, J., and Argos, P. (1991a). Side-chain clusters in protein structures and their role in protein folding. J. Mol. Biol. 220, 151-171. Heringa, J., and Argos P. (1993b). A method to recognize distant repeats in protein sequences. Proteins Struct. Func. Genet. 17, 391-411. Heringa, J. (1994). The evolution and recognition of protein sequence repeats. Comp. Chem. 18, 233-243. Heringa, J., and Taylor, W. R. (1997). Three-dimensional domain duplication, swapping and stealing. Curr. Opin. Struct. Biol. 7, 416-421. Heringa, J. (1998) Detection of internal sequence repeats: how common are they? Curr. Opin. Struct. Biology, 8, 338-345. Heringa J. (1999) Two strategies for sequence comparison: Profile-preprocessed and secondary structure-induced multiple alignment. Comp. Chem. 23, 341-364. Notredame, C., Higgins D., and Heringa, J. (2000) T-Coffee: A novel method for fast and accurate multiple sequence alignment. J. Mol. Biol., 302, 205-217. Heringa, J. (2002) Local weighting schemes for protein multiple sequence alignment. Comput. Chem., 26, 459-477. George, R.A. and Heringa, J. (2002) SNAPDRAGON: A new method to predict protein structural domain boundaries from sequence data. J. Mol. Biol., 316, 839-851. George R.A. and Heringa J. (2002) Protein domain identification and improved sequence similarity searching using PSI-BLAST, Proteins: Struct. Func. Gen. 48, 672-681. Szklarczyk, R. and Heringa, J. (2004) Tracking repeats using significance and transitivity. Bioinformatics 20 Suppl. 1, i311-i317. Lin K., Simossis V.A., Taylor W.R. and Heringa J. (2005) A Simple and Fast Secondary Structure Prediction Algorithm using Hidden Neural Networks. Bioinformatics. 21(2):152-9. Kleinjung, J., Romein, J., Lin, K., and Heringa J. (2004) Contact-based sequence alignment. Nucl. Acids Res. 32(8), 2464- 2473. Simossis V.A., Kleinjung, J. and Heringa J. (2005) Homology-extended sequence alignment. Nucleic Acids Res., 33(3):816-824. Click here for further references Selected methods produced over the years (IBIVU web services): REPRO - recognition of distant repeats in a single protein sequence TRUST - recognition of repeats on a genomic scale CLUSPROT - delineation of densely packed (side-chain) clusters in protein 3D structures OBSTRUCT - construction of largest possible protein sequence data sets based on sequence similarity and 3D structural features. SSPRED - Protein secondary structure prediction. PRALINE multiple sequence alignment toolkit T-COFFEE - multiple sequence alignment SnapDRAGON - Protein domain boundary prediction  using 3D model building consistency based on multiple alignments and secondary structure prediction DOMAINATION - Protein domain boundary prediction integrating the PSI-BLAST method with on-the-fly domain boundary recognition. Scooby Do - Protein domain boundary prediction based on a model of the distribution hydrophobic amino acids along the protein sequence CAO - Contact Accepted mutatiOn: a new HMM-based mutation scheme for evolutionary probabilities of residue 3D contact preservation, integrated in a method to assess the quality of alignments where the structure is known for one or more input sequences. AliCAO: a new alignment technique that uses the CAO evolutionary propensities associated with the residue contact network of a single protein in order to align a set of sequences. The alignments have better quality than those that are only based on sequence information and approach the quality of structural alignments based on protein 3D superpositioning.

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