Carl F Kesselman

About

Carl Kesselman leads ISI's Informatics Systems Research division. Created to understand how to build informatics systems that can help tackle the hardest problems of great societal impact, the work of the division spans grid computing, information security, service-oriented architectures, and sociotechnical systems and reproducibility.

Research topics

• Computer Science
• Biology
• Database
• Data science
• Data Mining
• World Wide Web
• Programming language
• Genetics
• Computational biology

Selected publications

• FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

  Development · 2020 · 56 citations

  The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a 'big data' resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote inte…

  DOI

• Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types

  Cell Reports · 2020 · 38 citations

  Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a sca…

  DOI

• FaceBase: A Community-Driven Hub for Data-Intensive Research

  Journal of Dental Research · 2022-07-31 · 14 citations

  reviewOpen access

  The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository…

  PublisherOA PDFDOI

• PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

  Journal of Molecular Biology · 2025-01-27 · 11 citations

  articleOpen access

  • Structures determined by integrative/hybrid methods (IHM) are archived alongside experimental structures in PDB as PDB-IHM. • These structures are processed by PDB-IHM in parallel to the wwPDB OneDep system and disseminated synchronously with PDB. • Integrative structures are assigned PDB accession codes and digital object identifiers. • PDB-IHM provides an API for depositing collections of structures and the workflows include generation of validation reports. • Integrative structures can be a…

  PublisherDOI

• IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods

  Journal of Molecular Biology · 2024-03-18 · 10 citations

  articleOpen access

  IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures o…

  PublisherOA PDFDOI

Recent grants

• NIH Grant U54CA143907

  NIH · $5.8M · 2016

• NIH Grant U24RR025736

  NIH · $20.5M · 2013

• Collaborative Research: Personalizing Recommendations in a Large-scale Education Analytics Pipeline

  NSF · $100k · 2015–2017

Frequent coauthors

• Ian Foster

  University of Illinois Chicago

  188 shared

• Ewa Deelman

  73 shared

• Ann Chervenak

  54 shared

• Karl Czajkowski

  University of Southern California

  46 shared

• Steven Tuecke

  University of Chicago

  39 shared

• Robert Schuler

  University of Southern California

  36 shared

• Laura Pearlman

  30 shared

• Gurmeet Singh

  Indian Institute of Wheat and Barley Research

  26 shared

Labs

• Informatics Systems Research divisionPI

Education

• Ph.D, Computer Science

  University of California Los Angeles

  1991

• Masters of Science, Electrical Engineering

  University of Southern California

  1984

• BSEE, Electrical Engineering

  University at Buffalo - The State University of New York

  1982

Awards & honors

• Lovelace Medal from the British Computer Society
• Goode Memorial Award from the IEEE Computer Society

Similar researchers at University of Southern California

• Jong-Shi Pangh-73
• Maged M. Dessoukyh-51
• Sheldon Mark Rossh-51