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MFM FELLOWSHIP FACULTY
ADI LAURENTIU TARCA, Ph.D.

Wayne State University/Perinatology Research Branch - Bioinformatics Director, Adi LaurentiuTarca, Ph.D.Title

  • Professor, Department of Obstetrics and Gynecology, Wayne State School of Medicine;
    Adjunct Professor, Department of Computer Science, Wayne State College of Engineering;

Education and Training

  • B.Sc. - Chemical Engineering, "Politehnica" University, Bucharest, Romania
  • M.Sc. - Electrochemistry, National Polytechnic Institute of Grenoble, France
  • Ph.D. - Chemical Engineering, Laval University, Quebec, Canada
  • Postdoctoral training - Bioinformatics, Laval University, Quebec, Canada

Research Accomplishments

  • Developed and applied neural network modeling and genetic algorithm optimization to engineering problems
  • Developed genomics data analysis methods and software packages available in Bioconductor including for:
    -normalization of microarray data (nnNorm)
    -analysis of signaling pathways (SPIA)
    -analysis of gene sets (PADOG)
    -predictive modeling (maPredictDSC)
  • Developed a customized standard for fetal growth assessment
  • Received multiple top awards in international systems biology/machine learning competitions sbv IMPROVER challenges and DREAM challenges
  • Developed the DREAM Preterm Birth Prediction Challenge to identify transcriptional markers for pregnancy dating and assessment of the risk of preterm birth

Awards and Recognitions

  • Funding NSERC (Canada) for Ph.D., Laval University, 2001 - 2003
  • Scholarship CNRS (France) for M.Sc., I.N.P. Grenoble, 2000
  • Scholarship TEMPUS (European Community) for M.Sc., I.N.P. Grenoble, 1999 - 2000
  • Scholarship TEMPUS for internship, U.S.T. Lille, 1997
  • Scholarship for Performance, U.P. Bucharest, 1998 - 1999

Research Interests

  • Methods for genomics data analysis and interpretation
  • Machine learning
  • Biomarkers in obstetrics
  • Personalized medicine

Selected Publications

  • Tarca AL, Romero R, Xu Z, Gomez-Lopez N, Erez O, Hsu CD, Hassan SS, Carey VJ. Targeted expression profiling by RNA-Seq improves detection of cellular dynamics during pregnancy and identifies a role for T cells in term parturition. Sci Rep; Sci Rep. 2019 Jan 29;9(1):848.
  • Tarca AL, Romero R, Gudicha DW, Erez O, Hernandez-Andrade E, Yeo L, Bhatti G, Pacora P, Maymon E, Hassan SS. A new customized fetal growth standard for African American women: the PRB/NICHD Detroit study. Am J Obstet Gynecol; 218(2S):S679-S91 e4, 2018.
  • Tarca AL, Fitzgerald W, Chaemsaithong P, Xu Z, Hassan SS, Grivel JC, Gomez-Lopez N, Panaitescu B, Pacora P, Maymon E, Erez O, Margolis L, Romero R. The cytokine network in women with an asymptomatic short cervix and the risk of preterm delivery. Am J Reprod Immunol, 2017.
  • Romero R, Erez O, Maymon E, Chaemsaithong P, Xu Z, Pacora P, Chaiworapongsa T, Done B, Hassan SS, Tarca AL. The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study. Am J Obstet Gynecol, 217(1):67.e1-67.e21, 2017.
  • Erez O, Romero R, Maymon E, Chaemsaithong P, Done B, Pacora P, Panaitescu B, Chaiworapongsa T, Hassan SS, Tarca AL. The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study. PLoS One;12(7):e0181468, 2017.
  • Tarca AL, Lauria M, Unger M, Bilal E, Boue S, Kumar Dey K, Hoeng J, Koeppl H, Martin F, Meyer P, Nandy P, Norel R, Peitsch M, Rice JJ, Romero R, Stolovitzky G, Talikka M, Xiang Y, Zechner C, Collaborators ID. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinformatics;29(22):2892-9, 2013.
  • Tarca AL, Draghici S, Bhatti G, Romero R. Down-weighting overlapping genes improves gene set analysis. BMC Bioinformatics;13:136, 2012.
  • Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics;25(1):75-82, 2009.
  • Tarca AL, Carey VJ, Chen XW, Romero R, Draghici S. Machine learning and its applications to biology. PLoS Comput Biol;3(6):e116, 2007.

Courses

  • Bioinformatics: theory and practice (MGG 7050)
  • Bioinformatics I (CSC 7301)
  • Bioinformatics II (CSC 7410)
  • Computer Applications in Molecular Genetics (MBG 8680)