Michael M. Hoffman
Michael M. Hoffman
Scientist, Princess Margaret Cancer Centre/Associate Professor, University of Toronto
Verified email at utoronto.ca - Homepage
Cited by
Cited by
An integrated Encyclopedia of DNA Elements in the human genome
ENCODE Project Consortium
Nature 489 (7414), 57-74, 2012
Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution
International Chicken Genome Sequencing Consortium
Nature 432 (7018), 695-716, 2004
ChIP-seq guidelines and practices used by the ENCODE and modENCODE consortia
SG Landt, GK Marinov, A Kundaje, P Kheradpour, F Pauli, S Batzoglou, ...
Genome Research 22 (9), 1813-31, 2012
A user's guide to the encyclopedia of DNA elements (ENCODE)
ENCODE Project Consortium
PLoS biol 9 (4), e1001046, 2011
Opportunities and obstacles for deep learning in biology and medicine. bioRxiv
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
New York: Wiley, 2017
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
MM Hoffman, OJ Buske, J Wang, Z Weng, JA Bilmes, WS Noble
Nature Methods 9 (5), 473, 2012
Integrative annotation of chromatin elements from ENCODE data
MM Hoffman, J Ernst, SP Wilder, A Kundaje, RS Harris, M Libbrecht, ...
Nucleic Acids Res 41 (2), 827-841, 2013
Comparative analysis of metazoan chromatin organization
JWK Ho, YL Jung, T Liu, BH Alver, S Lee, K Ikegami, KA Sohn, A Minoda, ...
Nature 512 (7515), 449-452, 2014
Sensitive tumour detection and classification using plasma cell-free DNA methylomes
SY Shen, R Singhania, G Fehringer, A Chakravarthy, MHA Roehrl, ...
Nature 563 (7732), 579-583, 2018
AANT: the Amino Acid–Nucleotide Interaction Database
MM Hoffman, MA Khrapov, JC Cox, J Yao, L Tong, AD Ellington
Nucleic Acids Research 32 (Database issue), D174-D181, 2004
Extending reference assembly models
DM Church, VA Schneider, KM Steinberg, MC Schatz, AR Quinlan, ...
Genome Biol 16, 13, 2015
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
M Zitnik, F Nguyen, B Wang, J Leskovec, A Goldenberg, MM Hoffman
Information Fusion 50, 71-91, 2019
Statistical Inference, Learning and Models in Big Data
B Franke, JF Plante, R Roscher, A Lee, C Smyth, A Hatefi, F Chen, E Gil, ...
Int Stat Rev, in press, 2016
Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell type-specific expression
MW Libbrecht, F Ay, MM Hoffman, DM Gilbert, JA Bilmes, WS Noble
Genome Res 25 (4), 544-557, 2015
A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data
X Chen, MM Hoffman, JA Bilmes, JR Hesselberth, WS Noble
Bioinformatics 26 (12), i334-i342, 2010
Classification and interaction in random forests
D Denisko, MM Hoffman
Proceedings of the National Academy of Sciences 115 (8), 1690-1692, 2018
Estimating the neutral rate of nucleotide substitution using introns
MM Hoffman, E Birney
Molecular Biology and Evolution 24 (2), 522-531, 2007
Umap and Bismap: quantifying genome and methylome mappability
M Karimzadeh, C Ernst, A Kundaje, MM Hoffman
Nucleic acids research 46 (20), e120-e120, 2018
An effective model for natural selection in promoters
MM Hoffman, E Birney
Genome Research 20 (5), 685-692, 2010
ChromNet: learning the human chromatin network from all ENCODE ChIP-seq data
SM Lundberg, WB Tu, B Raught, LZ Penn, MM Hoffman, SI Lee
Genome Biol 17, 82, 2016
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