About

David S. Roos, Ph.D., is the E. Otis Kendall Professor of Biology at the University of Pennsylvania's Department of Biology. His research interests encompass molecular parasitology, host-pathogen interactions, drug targets and resistance mechanisms, evolution of eukaryotic cells, and organellar function. His laboratory employs techniques in cell biology, molecular genetics, biochemistry, and genomics to study protozoan parasites, particularly within the phylum Apicomplexa, which includes parasites such as Plasmodium falciparum and Toxoplasma gondii. These parasites are responsible for diseases like malaria and toxoplasmosis, which have significant health impacts globally. Dr. Roos's work focuses on understanding parasite biology, drug resistance, and the evolution and function of eukaryotic organelles, including the apicoplast. His research also involves computational biology, including genome sequencing, database mining, and the development of analytical tools for genomic datasets. His contributions include elucidating mechanisms of parasite differentiation, immune evasion, and organellar targeting, advancing the understanding of protozoan parasite biology and host interactions.

Research topics

• Biology
• Genetics
• Computational biology
• Cell biology
• Molecular biology

Selected publications

• The promise of AlphaFold for gene structure annotation

  Nucleic Acids Research · 2025-10-21

  articleOpen access

  Most new genomes lack annotation, automated methods are error-prone, and few genomes are ever manually curated due to time and cost. Protein structure predictions may offer a new route to assess and improve gene models without requiring experimental data. Here, we explore whether scores from protein structure prediction can aid in scoring gene model quality. We chose three species (Fusarium graminearum, Toxoplasma gondii, and Aspergillus fumigatus) from the VEuPathDB database that have collectively undergone more than 1000 manual curation events. We modelled translations of the gene models with AlphaFold 3, before and after curation, collecting various scores. Then we carried out structure searching of the PDB with Foldseek and sequence-based domain identification using InterProScan. We profiled the scores produced by these methods to identify those best for gene model assessment. AlphaFold 3 scores strongly favoured manually improved over pre-improvement gene models, supporting 65-84% of manually-curated changes. Combining scores across multiple tools (AlphaFold 3, Foldseek and InterProScan) provided further improvements in model scoring. Overall, the most discriminative scores combined the outputs of AlphaFold 3 and Foldseek. Importantly, we find that scores from the much faster Protenix-Mini retain the same discriminatory power as those from AlphaFold 3. Our results, therefore, highlight the potential of scores derived from deep learning-based protein structure prediction for scoring gene models in the absence of experimental data.

  PublisherDOI

• VEuPathDB Resources: A Platform for Free Online Data Exploration, Integration, and Analysis

  Methods in molecular biology · 2024-01-01 · 12 citations

  articleSenior author
  PublisherDOI

• What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species

  Genetics · 2024-03-26 · 45 citations

  articleOpen access

  FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.

  PublisherOA PDFDOI

• TriTrypDB: An integrated functional genomics resource for kinetoplastida

  PLoS neglected tropical diseases · 2023-01-19 · 110 citations

  articleOpen accessCorresponding

  Parasitic diseases caused by kinetoplastid parasites are a burden to public health throughout tropical and subtropical regions of the world. TriTrypDB (https://tritrypdb.org) is a free online resource for data mining of genomic and functional data from these kinetoplastid parasites and is part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org). As of release 59, TriTrypDB hosts 83 kinetoplastid genomes, nine of which, including Trypanosoma brucei brucei TREU927, Trypanosoma cruzi CL Brener and Leishmania major Friedlin, undergo manual curation by integrating information from scientific publications, high-throughput assays and user submitted comments. TriTrypDB also integrates transcriptomic, proteomic, epigenomic, population-level and isolate data, functional information from genome-wide RNAi knock-down and fluorescent tagging, and results from automated bioinformatics analysis pipelines. TriTrypDB offers a user-friendly web interface embedded with a genome browser, search strategy system and bioinformatics tools to support custom in silico experiments that leverage integrated data. A Galaxy workspace enables users to analyze their private data (e.g., RNA-sequencing, variant calling, etc.) and explore their results privately in the context of publicly available information in the database. The recent addition of an annotation platform based on Apollo enables users to provide both functional and structural changes that will appear as 'community annotations' immediately and, pending curatorial review, will be integrated into the official genome annotation.

  PublisherDOI

• VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023

  Nucleic Acids Research · 2023-11-11 · 240 citations

  articleOpen access

  The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes.

  PublisherOA PDFDOI

• Structuration spatiale des principaux poissons démersaux autour de l’île de la Réunion à partir de la formeexterne de leurs otolithes

  HAL (Le Centre pour la Communication Scientifique Directe) · 2022-03-14

  article

  International audience

  Publisher

• The Quest for Orthologs orthology benchmark service in 2022

  Nucleic Acids Research · 2022-05-01 · 95 citations

  reviewOpen access

  The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.

  PublisherOA PDFDOI

• Cooperation in Countering Artemisinin Resistance in Africa: Learning from COVID-19

  American Journal of Tropical Medicine and Hygiene · 2022-04-12 · 11 citations

  editorialOpen access
  PublisherDOI

• Additional file of A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

  Open MIND · 2021-01-01

  datasetSenior author

  Additional file of A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

  DOI

• A Robust Implementation of a Reynolds Stress Model for Turbomachinery Applications in a Coupled Solver Environment

  2021-07-16 · 1 citations

  preprint
  PublisherDOI

Recent grants

• NIH Grant R37AI028724

  NIH · $4.6M · 2009

• NIH Grant R01AI028724

  NIH · $1.2M · 1998

Frequent coauthors

• Brian P. Brunk

  University of Pennsylvania

  161 shared

• Jessica C. Kissinger

  University of Georgia

  147 shared

• Omar S. Harb

  University of Pennsylvania

  120 shared

• Christian J. Stoeckert

  University of Pennsylvania

  111 shared

• Matthew Berriman

  University of Glasgow

  75 shared

• L. David Sibley

  South China Agricultural University

  69 shared

• John Iodice

  University of Pennsylvania

  66 shared

• Cristina Aurrecoechea

  University of Georgia

  66 shared

Education

• Helen Hay Whitney Postdoctoral Fellow, Biological Sciences

  Stanford University

  1988

• PhD, Virology & Cell Biology

  The Rockefeller University

  1984

• AB, Biology & Art History

  Harvard College

  1979

• Special Student (no degree), Mathematics

  Dartmouth College

  1973