J
Jaap Heringa
Researcher at VU University Amsterdam
Publications - 168
Citations - 20564
Jaap Heringa is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Multiple sequence alignment & Sequence alignment. The author has an hindex of 40, co-authored 163 publications receiving 16406 citations. Previous affiliations of Jaap Heringa include University of Cambridge & Academic Center for Dentistry Amsterdam.
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The FAIR Guiding Principles for scientific data management and stewardship
Mark Wilkinson,Michel Dumontier,IJsbrand Jan Aalbersberg,Gabrielle Appleton,Myles Axton,Arie Baak,Niklas Blomberg,Jan-Willem Boiten,Luiz Olavo Bonino da Silva Santos,Philip E. Bourne,Jildau Bouwman,Anthony J. Brookes,Timothy Clark,Mercè Crosas,Ingrid Dillo,Olivier G. Dumon,Scott C. Edmunds,Chris T. Evelo,Richard Finkers,Alejandra Gonzalez-Beltran,Alasdair J. G. Gray,Paul Groth,Carole Goble,Jeffrey S. Grethe,Jaap Heringa,Peter A C 't Hoen,Rob Hooft,Tobias Kuhn,Ruben Kok,Joost N. Kok,Scott J. Lusher,Maryann E. Martone,Albert Mons,Abel L. Packer,Bengt Persson,Philippe Rocca-Serra,Marco Roos,Rene van Schaik,Susanna-Assunta Sansone,Erik Anthony Schultes,Thierry Sengstag,Ted Slater,George Strawn,Morris A. Swertz,Mark Thompson,Johan van der Lei,Erik M. van Mulligen,Jan Velterop,Andra Waagmeester,Peter Wittenburg,Katherine Wolstencroft,Jun Zhao,Barend Mons,Barend Mons +53 more
TL;DR: The FAIR Data Principles as mentioned in this paper are a set of data reuse principles that focus on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.
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T-Coffee: A novel method for fast and accurate multiple sequence alignment.
TL;DR: A new method for multiple sequence alignment that provides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives but avoids the most serious pitfalls caused by the greedy nature of this algorithm.
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PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information.
V. A. Simossis,Jaap Heringa +1 more
TL;DR: PRALINE can integrate information from database homology searches to generate a homology-extended multiple alignment and provides a choice of seven different secondary structure prediction programs that can be used individually or in combination as a consensus for integrating structural information into the alignment process.
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An analysis of protein domain linkers: their classification and role in protein folding
Richard A. George,Jaap Heringa +1 more
TL;DR: A linker database intended for the rational design of linkers for domain fusion is constructed and two main types of linker were identified; helical and non-helical.
Journal ArticleDOI
A simple and fast secondary structure prediction method using hidden neural networks
TL;DR: A secondary structure prediction method YASPIN that unlike the current state-of-the-art methods utilizes a single neural network for predicting the secondary structure elements in a 7-state local structure scheme and then optimizes the output using a hidden Markov model, which results in providing more information for the prediction.