Chen Yanover
	Program in Computational Biology Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N., M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 email: cyanover at fhcrc dot org Tel: 206-667-7661 Fax: 206-667-1319		CV Research interests Publications Book chapters Software and web-based tools Personal

Research interests

• Characterization, prediction and design of macromolecular interactions, in particular those mediated by a linear sequence motif (e.g., peptide or a DNA molecule)
• Methodologies for multi-state protein design, where alternative conformations of the target structure or its interactions with various binding partners are taken into account
• Computational characterization of peptide-MHC binding landscapes, investigating their association with diverse immunological conditions: disease control, immunogenicity of protein therapeutics, and graft versus host disease
• Development of machine learning tools and, specifically, Markov random fields algorithms, for structural biology tasks, including atomic-level structure prediction and design

Publications (Google scholar, Web of Knowledge, PubMed)

HLA mismatches and hematopoietic cell transplantation: structural simulations assess the impact of changes in peptide binding specificity on transplant outcome

Chen Yanover, Mari Malkki, Ted Gooley, Effie Petersdorf, Stephen Spellman, Andrea Velardi, Peter Bardy, Alejandro Madrigal, Philip Bradley
Immunome Research, 7(2):24, 2011 (html, PDF, PubMed)

Machine learning competition in immunology - Prediction of HLA class I binding peptides

Guang Lan Zhang, Hifzur Rahman Ansari, Phil Bradley, Gavin C. Cawley, Tomer Hertz, Xihao Hu, Nebojsa Jojic, Yohan Kim, Oliver Kohlbacher, Ole Lund, Claus Lundegaard, Craig A. Magaret, Morten Nielsen, Harris Papadopoulos, G.P.S. Raghava, Vider-Shalit Tal, Li C. Xue, Chen Yanover, Shanfeng Zhu, Michael T. Rock, James E. Crowe Jr., Christos Panayiotou, Marios M. Polycarpou, Wlodzislaw Duch, Vladimir Brusic
Journal of Immunological Methods, 374(1-2):1-4, 2011 (html, PubMed)

Pharmacogenetics and the immunogenicity of protein therapeutics

Chen Yanover, Nisha Jain, Glenn Pierce, Tom E Howard, Zuben E Sauna
Nature Biotechnology 29:870-873, 2011 (html, PDF, PubMed)

Large-scale characterization of peptide-MHC binding landscapes with structural simulations

Chen Yanover, Philip Bradley
PNAS, 108:6981-6986, 2011 (html, PDF, PubMed)

Extensive protein and DNA backbone sampling improves structure-based specificity prediction for C2H2 zinc fingers

Chen Yanover, Philip Bradley
Nucleic Acids Research, 39:4564-4576, 2011 (html, PDF, PubMed, F1000)

Haemophilia management: Time to get personal?

Tom E. Howard, Chen Yanover, Johnny Mahlangu, Amanda Krause, Kevin R. Viel, Carol K. Kasper, Kathleen P. Pratt
Haemophilia 17:721-728, 2011 (html, PubMed)

Optimizing Energy Functions for Protein-Protein Interface Design

Oz Sharabi*, Chen Yanover*, Ayelet Dekel, Julia M. Shifman
Journal of Computational Chemistry, 32(1):23-32, 2011 (html, PubMed)

How do amino acid mismatches affect the outcome of hematopoietic cell transplants? A structural perspective

Chen Yanover, Mari Malkki, Ted Gooley, Effie Petersdorf, Stephen Spellman, Andrea Velardi, Peter Bardy, Alejandro Madrigal, Philip Bradley
Immunoinformatics and Computational Immunology Workshop, ACM International Conference on Bioinformatics and Computational Biology, pp. 627-633, 2010 (html)

Inferring PDZ domain multi-mutant binding preferences from single-mutant data

Elena Zaslavsky, Philip Bradley, Chen Yanover
PLoS One, 5(9):e12787, 2010 (html, PubMed)
Best performer in DREAM4 challenge: Prediction of Peptide Recognition in PDZ domains

SPRINT: side-chain prediction inference toolbox for multistate protein design

Menachem Fromer, Chen Yanover, Amir Harel, Ori Shachar, Yair Weiss, Michal Linial
Bioinformatics. 26(19):2466-7, 2010 (html, PubMed)

Design of multi-specific protein sequences using probabilistic graphical modeling

Menachem Fromer, Chen Yanover, Michal Linial
Proteins: Structure, Function, and Bioinformatics, 78(3):530-547, 2010 (html, PubMed)

M are better than one: an ensemble-based motif finder and its application to regulatory element prediction

Chen Yanover, Mona Singh, Elena Zaslavsky
Bioinformatics, 25(7):868-874, 2009 (html, PDF, Data, PubMed)

Accurate Prediction for Atomic-Level Protein Design and its Application in Diversifying the Near-Optimal Sequence Space

Menachem Fromer, Chen Yanover
Proteins: Structure, Function, and Bioinformatics, 75(3):682-705, 2009 (html, PubMed)

Minimizing and Learning Energy Functions for Side-Chain Prediction

Chen Yanover, Ora Schueler-Furman, Yair Weiss
Journal of Computational Biology. September 2008, 15(7): 899-911 (html, Data, PubMed, F1000)
Preliminary version: RECOMB 2007 (PDF)

A computational framework to empower probabilistic protein design

Menachem Fromer, Chen Yanover
Bioinformatics, 24(13):i214-222, 2008 (html, PubMed)

MAP Estimation, Linear Programming and Belief Propagation with Convex Free Energies

Yair Weiss, Chen Yanover, Talya Meltzer
UAI 2007 (Postscript, PDF)

Dead-End Elimination for Multi-state Protein Design

Chen Yanover, Menachem Fromer, Julia M. Shifman
Journal of Computational Chemistry, 28(13):2122-2129, October 2007 (PubMed)

Identifying HLA Supertypes by Learning Distance Functions

Tomer Hertz, Chen Yanover
Bioinformatics, 23(2):e148-155, 2007 (html, PDF, PubMed)

Linear Programming Relaxations and Belief Propagation — An Empirical Study

Chen Yanover, Talya Meltzer, Yair Weiss
Journal of Machine Learning Research, Special Topic on Machine Learning and Optimization, Sep. 2006 (PDF, Data)

PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions

Tomer Hertz, Chen Yanover
BMC Bioinformatics 2006, 7(Suppl 1):S3,
NIPS workshop on New Problems and Methods in Computational Biology Whistler, Canada. December 2004 (html, PDF, PubMed)

Globally optimal solutions for energy minimization in stereo vision using reweighted belief propagation

Talya Meltzer, Chen Yanover, Yair Weiss
ICCV 2005 (Postscript, PDF)

Predicting Protein-Peptide Binding Affinity by Learning Peptide-Peptide Distance Functions

Chen Yanover, Tomer Hertz
RECOMB 2005 (Postscript, PDF)

Finding the M Most Probable Configurations Using Loopy Belief Propagation

Chen Yanover, Yair Weiss
NIPS 2003 (Postscript, PDF)
A short note on BMMF with ties

Approximate Inference and Protein Folding

Chen Yanover, Yair Weiss
NIPS 2002 (Postscript, PDF)
Extended version: Approximate Inference and Side-chain Prediction (Leibniz Center, Technical Report 2007-30, Data)

Computer Analysis of the Entire Budding Yeast Genome for Putative Targets of the GCN4 Transcription Factor

Oren Schuldiner, Chen Yanover, Nissim Benvenisty
Curr Genet 33(1):16-20, Jan 1998 (PubMed)

Book chapters

Linear Programming and Variants of Belief Propagation

Yair Weiss, Chen Yanover, Talya Meltzer
In: Blake A, Rother C, Kohli P, editors, Advances in Markov Random Fields for Vision and Image Processing, MIT Press, 2011

Prediction of Low Energy Protein Side Chain Configurations using Markov Random Fields

Chen Yanover, Menachem Fromer
In: Hamelryck T, Mardia KV, Ferkinghoff-Borg J, editors, Bayesian Methods in Structural Bioinformatics, Berlin, Germany: Springer-Verlag, 2012

Software and web-based tools

SPRINT: the Side-chain Prediction Inference Toolbox

Best Max-Marginal First algorithm for finding the M most probable configurations (matlab implementation)

Matlab sparse cell class (version 2)

Stereo package for finding globally optimal solutions for energy minimization in stereo vision

PepDist webserver

Personal

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