Now showing items 1-14 of 14

    • A branching process model for flow cytometry and budding index measurements in cell synchrony experiments. 

      Haase, SB; Hartemink, Alexander J; Iversen, Edwin S; Orlando, DA (Ann Appl Stat, 2009)
      We present a flexible branching process model for cell population dynamics in synchrony/time-series experiments used to study important cellular processes. Its formulation is constructive, based on an accounting of the unique ...
    • A framework for integrating the songbird brain. 

      Carninci, P; Dietrich, F; Hartemink, Alexander J; Hayashizaki, Y; Jarvis, Erich David; Lin, S; McConnell, P; ... (15 authors) (J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 2002-12)
      Biological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird ...
    • A nucleosome-guided map of transcription factor binding sites in yeast. 

      Gordân, R; Hartemink, Alexander J; Narlikar, L (PLoS Comput Biol, 2007-11)
      Finding functional DNA binding sites of transcription factors (TFs) throughout the genome is a crucial step in understanding transcriptional regulation. Unfortunately, these binding sites are typically short and degenerate, ...
    • Advances to Bayesian network inference for generating causal networks from observational biological data. 

      Hartemink, Alexander J; Jarvis, Erich David; Smith, VA; Wang, PP; Yu, J (Bioinformatics, 2004-12-12)
      MOTIVATION: Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise ...
    • Computational inference of neural information flow networks. 

      Hartemink, Alexander J; Jarvis, Erich David; Smith, VA; Smulders, TV; Yu, J (PLoS Comput Biol, 2006-11-24)
      Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow ...
    • Convergent transcriptional specializations in the brains of humans and song-learning birds. 

      Bakken, T; Bernard, A; Bongaarts, A; Ganapathy, G; Gilbert, M Thomas P; Hara, E; Hartemink, Alexander J; ... (25 authors) (Science, 2014-12-12)
      Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes ...
    • Core and region-enriched networks of behaviorally regulated genes and the singing genome. 

      Audet, JN; Blatti, Charles A; Hartemink, Alexander J; Howard, JT; Jarvis, Erich David; Kellis, M; Liu, F; ... (14 authors) (Science, 2014-12-12)
      Songbirds represent an important model organism for elucidating molecular mechanisms that link genes with complex behaviors, in part because they have discrete vocal learning circuits that have parallels with those that ...
    • Domain-oriented edge-based alignment of protein interaction networks. 

      Guo, X; Hartemink, Alexander J (Bioinformatics, 2009-06-15)
      MOTIVATION: Recent advances in high-throughput experimental techniques have yielded a large amount of data on protein-protein interactions (PPIs). Since these interactions can be organized into networks, and since separate ...
    • Evaluating functional network inference using simulations of complex biological systems. 

      Hartemink, Alexander J; Jarvis, Erich David; Smith, VA (Bioinformatics, 2002)
      MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological ...
    • Finding regulatory DNA motifs using alignment-free evolutionary conservation information. 

      Gordân, R; Hartemink, Alexander J; Narlikar, L (Nucleic Acids Res, 2010-04)
      As an increasing number of eukaryotic genomes are being sequenced, comparative studies aimed at detecting regulatory elements in intergenic sequences are becoming more prevalent. Most comparative methods for transcription ...
    • Influence of network topology and data collection on network inference. 

      Hartemink, Alexander J; Jarvis, Erich David; Smith, VA (Pac Symp Biocomput, 2003)
      We recently developed an approach for testing the accuracy of network inference algorithms by applying them to biologically realistic simulations with known network topology. Here, we seek to determine the degree to which ...
    • Learning a hybrid architecture for sequence regression and annotation 

      Carin, Lawrence; Hartemink, Alexander J; Henao, R; Zhang, Y; Zhong, J (30th AAAI Conference on Artificial Intelligence, AAAI 2016, 2016-01-01)
      © Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.When learning a hidden Markov model (HMM), sequential observations can often be complemented by real-valued ...
    • SLICER: inferring branched, nonlinear cellular trajectories from single cell RNA-seq data. 

      Hartemink, Alexander J; Prins, JF; Welch, JD (Genome Biol, 2016-05-23)
      Single cell experiments provide an unprecedented opportunity to reconstruct a sequence of changes in a biological process from individual "snapshots" of cells. However, nonlinear gene expression changes, genes unrelated ...
    • Stability selection for regression-based models of transcription factor-DNA binding specificity. 

      Engelhardt, BE; Gordân, R; Hartemink, Alexander J; Horton, J; Mordelet, F (Bioinformatics, 2013-07-01)
      MOTIVATION: The DNA binding specificity of a transcription factor (TF) is typically represented using a position weight matrix model, which implicitly assumes that individual bases in a TF binding site contribute independently ...