Alexander J. Hartemink

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Raluca GordanAssociate Professor, Duke UniversityEmail confirmado em duke.edu
Lawrence CarinDuke UniversityEmail confirmado em duke.edu
Balaji KrishnapuramIBM Watson HealthEmail confirmado em us.ibm.com
Erich JarvisRockefeller University, Duke University, HHMIEmail confirmado em rockefeller.edu
V Anne SmithSchool of Biology, University of St AndrewsEmail confirmado em st-andrews.ac.uk
David M. MacAlpineProfessor of Pharmacology and Cancer Biology, Duke UniversityEmail confirmado em duke.edu
Tommi JaakkolaMITEmail confirmado em csail.mit.edu
Mario A. T. FigueiredoInstituto de Telecomunicações, Instituto Superior Técnico, Universidade de LisboaEmail confirmado em tecnico.ulisboa.pt
Gregory CrawfordDuke UniversityEmail confirmado em duke.edu
Steven B. HaaseProfessor of Biology, Professor of Medicine, Duke UniversityEmail confirmado em duke.edu
Richard YoungProfessor of Biology, MITEmail confirmado em wi.mit.edu
Edwin S Iversen JrResearch Professor of Statistical Science, Duke UniversityEmail confirmado em stat.duke.edu
Randy JirtleProfessor of Epigenetics, NC State UniversityEmail confirmado em ncsu.edu
Leelavati NarlikarData Science, IISER PuneEmail confirmado em iiserpune.ac.in
David OrlandoMOMA TherapeuticsEmail confirmado em momatx.com
Jianling ZhongDuke UniversityEmail confirmado em alumni.duke.edu
Charles GersbachProfessor of Biomedical Engineering, Duke UniversityEmail confirmado em duke.edu
Andreas R PfenningAssociate Professor, Carnegie Mellon UniversityEmail confirmado em cmu.edu
Osceola Whitney, PhDCity College of the City University of New YorkEmail confirmado em ccny.cuny.edu
Jason HowardMiRXESEmail confirmado em mirxes.com

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Alexander J. Hartemink

Professor of Computer Science, Duke University

Email confirmado em cs.duke.edu - Página inicial

computational biology systems biology machine learning Bayesian statistics computational genomics


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia SG Landt, GK Marinov, A Kundaje, P Kheradpour, F Pauli, S Batzoglou, ... Genome Research 22 (9), 1813-1831, 2012	2358	2012
Sparse multinomial logistic regression: Fast algorithms and generalization bounds B Krishnapuram, L Carin, MAT Figueiredo, AJ Hartemink Pattern Analysis and Machine Intelligence, IEEE Transactions on 27 (6), 957-968, 2005	1134	2005
Advances to Bayesian network inference for generating causal networks from observational biological data J Yu, VA Smith, PP Wang, AJ Hartemink, ED Jarvis Bioinformatics 20 (18), 3594-3603, 2004	913	2004
Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks AJ Hartemink, DK Gifford, TS Jaakkola, RA Young Pacific Symposium on Biocomputing 2001 6, 422-433, 2001	593	2001
Convergent transcriptional specializations in the brains of humans and song-learning birds AR Pfenning, E Hara, O Whitney, MV Rivas, R Wang, PL Roulhac, ... Science 346 (6215), 1256846, 2014	533	2014
Computational and experimental identification of novel human imprinted genes PP Luedi, FS Dietrich, JR Weidman, JM Bosko, RL Jirtle, AJ Hartemink Genome Research 17 (12), 1723-1730, 2007	496	2007
Combining location and expression data for principled discovery of genetic regulatory network models AJ Hartemink, DK Gifford, TS Jaakkola, RA Young Pacific Symposium on Biocomputing 2002 7, 437-449, 2002	445	2002
Global control of cell-cycle transcription by coupled CDK and network oscillators DA Orlando, CY Lin, A Bernard, JY Wang, JES Socolar, ES Iversen, ... Nature 453 (7197), 944-947, 2008	397	2008
Genome-wide prediction of imprinted murine genes PP Luedi, AJ Hartemink, RL Jirtle Genome Research 15 (6), 875-884, 2005	354	2005
Synergistic and tunable human gene activation by combinations of synthetic transcription factors P Perez-Pinera, DG Ousterout, JM Brunger, AM Farin, KA Glass, F Guilak, ... Nature Methods 10 (3), 239-242, 2013	342	2013
Drosophila ORC localizes to open chromatin and marks sites of cohesin complex loading HK MacAlpine, R Gordân, SK Powell, AJ Hartemink, DM MacAlpine Genome Research 20 (2), 201-211, 2010	338	2010
Informative structure priors: Joint learning of dynamic regulatory networks from multiple types of data A Bernard, AJ Hartemink Pacific Symposium on Biocomputing 2005 10, 459-470, 2005	261	2005
Learning non-stationary dynamic Bayesian networks JW Robinson, AJ Hartemink Journal of Machine Learning Research 11 (12), 3647-3680, 2010	225	2010
A Bayesian approach to joint feature selection and classifier design B Krishnapuram, AJ Hartemink, L Carin, MAT Figueiredo Pattern Analysis and Machine Intelligence, IEEE Transactions on 26 (9), 1105 …, 2004	220	2004
Reverse engineering gene regulatory networks AJ Hartemink Nature Biotechnology 23 (5), 554-555, 2005	206	2005
Evaluating functional network inference using simulations of complex biological systems VA Smith, ED Jarvis, AJ Hartemink Bioinformatics 18 (S1), S216-S224, 2002	197	2002
Computational inference of neural information flow networks VA Smith, J Yu, TV Smulders, AJ Hartemink, ED Jarvis PLoS Computational Biology 2 (11), 1436-1449, 2006	194	2006
SLICER: Inferring branched, nonlinear cellular trajectories from single cell RNA-seq data JD Welch, AJ Hartemink, JF Prins Genome Biology 17 (106), 1-15, 2016	193	2016
Distinguishing direct versus indirect transcription factor–DNA interactions R Gordân, AJ Hartemink, ML Bulyk Genome Research 19 (11), 2090-2100, 2009	173	2009
MATCHER: Manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics JD Welch, AJ Hartemink, JF Prins Genome Biology 18 (138), 1-19, 2017	170	2017

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