Browsing by Author "Alterovitz, Gil"

Now showing items 1-10 of 10

    • An Automated Bayesian Framework for Integrative Gene Expression Analysis and Predictive Medicine 

      Parikh, Neena; Zollanvari, Amin; Alterovitz, Gil (American Medical Informatics Association, 2012)
      Motivation: This work constructs a closed loop Bayesian Network framework for predictive medicine via integrative analysis of publicly available gene expression findings pertaining to various diseases. Results: An automated ...

    • Automated Synthesis and Visualization of a Chemotherapy Treatment Regimen Network 

      Warner, Jeremy; Yang, Peter; Alterovitz, Gil (2013)
      Cytotoxic treatments for cancer remain highly toxic, expensive, and variably efficacious. Many chemotherapy regimens are never directly compared in randomized clinical trials (RCTs); as a result, the vast majority of ...

    • A Bayesian Translational Framework for Knowledge Propagation, Discovery, and Integration Under Specific Contexts 

      Deng, Michelle Rui; Zollanvari, Amin; Alterovitz, Gil (American Medical Informatics Association, 2012)
      The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts—rather than ...

    • Context-Specific Ontology Integration: A Bayesian Approach 

      Marwah, Kshitij; Katzin, Dustin; Zollanvari, Amin; Noy, Natalya F.; Ramoni, Marco; Alterovitz, Gil (American Medical Informatics Association, 2012)
      We introduce a principled computational framework and methodology for automated discovery of context-specific functional links between ontologies. Our model leverages over disparate free-text literature resources to score ...

    • Gene expression prediction using low-rank matrix completion 

      Kapur, Arnav; Marwah, Kshitij; Alterovitz, Gil (BioMed Central, 2016)
      Background: An exponential growth of high-throughput biological information and data has occurred in the past decade, supported by technologies, such as microarrays and RNA-Seq. Most data generated using such methods are ...

    • Nonlinear dimensionality reduction methods for synthetic biology biobricks’ visualization 

      Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil (BioMed Central, 2017)
      Background: Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately ...

    • On the Bayesian Derivation of a Treatment-based Cancer Ontology 

      Gao, Michael; Warner, Jeremy; Yang, Peter; Alterovitz, Gil (American Medical Informatics Association, 2014)
      Traditional cancer classifications are primarily based on anatomical locations. As knowledge is heavily compartmentalized in the oncological specialties, discovering new targets for existing drugs (drug inference) can take ...

    • Order-Disorder Interface Characterization Reveals Critical Factors for Disease and Drug Targets 

      Kallenbach, Jonah; Hsu, Wei-Lun; Dunker, A. Keith; Alterovitz, Gil (American Medical Informatics Association, 2013)
      Signal transduction pathways are of critical importance in disease and regulation of cellular functions. Proteins that do not fold to a state of stable tertiary structure, known as intrinsically disordered proteins, are ...

    • Rational Discovery of Antimetastatic Agents Targeting the Intrinsically Disordered Region of MBD2 

      Na, Insung; Alterovitz, Gil; Kim, Min Kyoung; Kim, Ji Sook; Son, Seung Han; Choi, Sungwoo; Lee, Seol Eui; Kim, Ji-Hun; Jang, Kiseok; Chen, Yu; van der Vaart, Arjan; Won, Hyung-Sik; Uversky, Vladamir; Kim, Chul Geon (American Association for the Advancement of Science (AAAS), 2019-11)
      Although intrinsically disordered protein regions (IDPRs) are commonly engaged in promiscuous protein-protein interactions (PPIs), using them as drug targets is challenging due to their extreme structural flexibility. We ...

    • Robust Prediction-Based Analysis for Genome-Wide Association and Expression Studies 

      K. Koppula, Skanda; Zollanvari, Amin; An, Ning; Alterovitz, Gil (American Medical Informatics Association, 2013)
      Here we describe a prediction-based framework to analyze omic data and generate models for both disease diagnosis and identification of cellular pathways which are significant in complex diseases. Our framework differs ...