Alexander J. Hartemink

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

Alexander J. Hartemink

Professor of Computer Science, Duke University

Verified email at cs.duke.edu - Homepage

computational biology systems biology machine learning Bayesian statistics computational genomics


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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	2320	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	1118	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	901	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	590	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	524	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	488	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	438	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	393	2008
Genome-wide prediction of imprinted murine genes PP Luedi, AJ Hartemink, RL Jirtle Genome Research 15 (6), 875-884, 2005	353	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	334	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	331	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	257	2005
Learning non-stationary dynamic Bayesian networks JW Robinson, AJ Hartemink Journal of Machine Learning Research 11 (12), 3647-3680, 2010	224	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	205	2005
Evaluating functional network inference using simulations of complex biological systems VA Smith, ED Jarvis, AJ Hartemink Bioinformatics 18 (S1), S216-S224, 2002	196	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	193	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	192	2016
Distinguishing direct versus indirect transcription factor–DNA interactions R Gordân, AJ Hartemink, ML Bulyk Genome Research 19 (11), 2090-2100, 2009	175	2009
Maximum likelihood estimation of optimal scaling factors for expression array normalization AJ Hartemink, DK Gifford, TS Jaakkola, RA Young Microarrays: Optical Technologies and Informatics, at the SPIE International …, 2001	165	2001

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