Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where John Iodice is active.

Publication


Featured researches published by John Iodice.


Nucleic Acids Research | 2009

PlasmoDB: a functional genomic database for malaria parasites

Cristina Aurrecoechea; John Brestelli; Brian P. Brunk; Jennifer Dommer; Steve Fischer; Bindu Gajria; Xin Gao; Alan R. Gingle; Gregory R. Grant; Omar S. Harb; Mark Heiges; Frank Innamorato; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; John A. Miller; Vishal Nayak; Cary Pennington; Deborah F. Pinney; David S. Roos; Chris Ross; Christian J. Stoeckert; Charles Treatman; Haiming Wang

PlasmoDB (http://PlasmoDB.org) is a functional genomic database for Plasmodium spp. that provides a resource for data analysis and visualization in a gene-by-gene or genome-wide scale. PlasmoDB belongs to a family of genomic resources that are housed under the EuPathDB (http://EuPathDB.org) Bioinformatics Resource Center (BRC) umbrella. The latest release, PlasmoDB 5.5, contains numerous new data types from several broad categories—annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution. Data in PlasmoDB can be queried by selecting the data of interest from a query grid or drop down menus. Various results can then be combined with each other on the query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.


Nucleic Acids Research | 2010

TriTrypDB: a functional genomic resource for the Trypanosomatidae

Martin Aslett; Cristina Aurrecoechea; Matthew Berriman; John Brestelli; Brian P. Brunk; Mark Carrington; Daniel P. Depledge; Steve Fischer; Bindu Gajria; Xin Gao; Malcolm J. Gardner; Alan R. Gingle; Greg Grant; Omar S. Harb; Mark Heiges; Christiane Hertz-Fowler; Robin Houston; Frank Innamorato; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; Flora J. Logan; John A. Miller; Siddhartha Mitra; Peter J. Myler; Vishal Nayak; Cary Pennington; Isabelle Phan; Deborah F. Pinney

TriTrypDB (http://tritrypdb.org) is an integrated database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. TriTrypDB is a collaborative project, utilizing the GUS/WDK computational infrastructure developed by the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org) to integrate genome annotation and analyses from GeneDB and elsewhere with a wide variety of functional genomics datasets made available by members of the global research community, often pre-publication. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ‘User Comments’ may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate.


Nucleic Acids Research | 2007

ToxoDB: an integrated Toxoplasma gondii database resource

Bindu Gajria; Amit Bahl; John Brestelli; Jennifer Dommer; Steve Fischer; Xin Gao; Mark Heiges; John Iodice; Jessica C. Kissinger; Aaron J. Mackey; Deborah F. Pinney; David S. Roos; Christian J. Stoeckert; Haiming Wang; Brian P. Brunk

ToxoDB (http://ToxoDB.org) is a genome and functional genomic database for the protozoan parasite Toxoplasma gondii. It incorporates the sequence and annotation of the T. gondii ME49 strain, as well as genome sequences for the GT1, VEG and RH (Chr Ia, Chr Ib) strains. Sequence information is integrated with various other genomic-scale data, including community annotation, ESTs, gene expression and proteomics data. ToxoDB has matured significantly since its initial release. Here we outline the numerous updates with respect to the data and increased functionality available on the website.


Current protocols in human genetics | 2011

Using OrthoMCL to assign proteins to OrthoMCL-DB groups or to cluster proteomes into new ortholog groups.

Steve Fischer; Brian P. Brunk; Feng Chen; Xin Gao; Omar S. Harb; John Iodice; Dhanasekaran Shanmugam; David S. Roos; Christian J. Stoeckert

OrthoMCL is an algorithm for grouping proteins into ortholog groups based on their sequence similarity. OrthoMCL-DB is a public database that allows users to browse and view ortholog groups that were pre-computed using the OrthoMCL algorithm. Version 4 of this database contained 116,536 ortholog groups clustered from 1,270,853 proteins obtained from 88 eukaryotic genomes, 16 archaean genomes, and 34 bacterial genomes. Future versions of OrthoMCL-DB will include more proteomes as more genomes are sequenced. Here, we describe how you can group your proteins of interest into ortholog clusters using two different means provided by the OrthoMCL system. The OrthoMCL-DB Web site has a tool for uploading and grouping a set of protein sequences, typically representing a proteome. This method maps the uploaded proteins to existing groups in OrthoMCL-DB. Alternatively, if you have proteins from a set of genomes that need to be grouped, you can download, install, and run the stand-alone OrthoMCL software.


Nucleic Acids Research | 2009

GiardiaDB and TrichDB: integrated genomic resources for the eukaryotic protist pathogens Giardia lamblia and Trichomonas vaginalis

Cristina Aurrecoechea; John Brestelli; Brian P. Brunk; Jane M. Carlton; Jennifer Dommer; Steve Fischer; Bindu Gajria; Xin Gao; Alan R. Gingle; Gregory R. Grant; Omar S. Harb; Mark Heiges; Frank Innamorato; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; John A. Miller; Hilary G. Morrison; Vishal Nayak; Cary Pennington; Deborah F. Pinney; David S. Roos; Chris Ross; Christian J. Stoeckert; Steven A. Sullivan; Charles Treatman; Haiming Wang

GiardiaDB (http://GiardiaDB.org) and TrichDB (http://TrichDB.org) house the genome databases for Giardia lamblia and Trichomonas vaginalis, respectively, and represent the latest additions to the EuPathDB (http://EuPathDB.org) family of functional genomic databases. GiardiaDB and TrichDB employ the same framework as other EuPathDB sites (CryptoDB, PlasmoDB and ToxoDB), supporting fully integrated and searchable databases. Genomic-scale data available via these resources may be queried based on BLAST searches, annotation keywords and gene ID searches, GO terms, sequence motifs and other protein characteristics. Functional queries may also be formulated, based on transcript and protein expression data from a variety of platforms. Phylogenetic relationships may also be interrogated. The ability to combine the results from independent queries, and to store queries and query results for future use facilitates complex, genome-wide mining of functional genomic data.


Nucleic Acids Research | 2010

EuPathDB: a portal to eukaryotic pathogen databases

Cristina Aurrecoechea; John Brestelli; Brian P. Brunk; Steve Fischer; Bindu Gajria; Xin Gao; Alan R. Gingle; Gregory R. Grant; Omar S. Harb; Mark Heiges; Frank Innamorato; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; John A. Miller; Vishal Nayak; Cary Pennington; Deborah F. Pinney; David S. Roos; Chris Ross; Ganesh Srinivasamoorthy; Christian J. Stoeckert; Ryan Thibodeau; Charles Treatman; Haiming Wang

EuPathDB (http://EuPathDB.org; formerly ApiDB) is an integrated database covering the eukaryotic pathogens of the genera Cryptosporidium, Giardia, Leishmania, Neospora, Plasmodium, Toxoplasma, Trichomonas and Trypanosoma. While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all these resources, and the opportunity to leverage orthology for searches across genera. The most recent release of EuPathDB includes updates and changes affecting data content, infrastructure and the user interface, improving data access and enhancing the user experience. EuPathDB currently supports more than 80 searches and the recently-implemented ‘search strategy’ system enables users to construct complex multi-step searches via a graphical interface. Search results are dynamically displayed as the strategy is constructed or modified, and can be downloaded, saved, revised, or shared with other database users.


Nucleic Acids Research | 2013

EuPathDB: The Eukaryotic Pathogen database

Cristina Aurrecoechea; Ana Barreto; John Brestelli; Brian P. Brunk; Shon Cade; Ryan Doherty; Steve Fischer; Bindu Gajria; Xin Gao; Alan R. Gingle; Gregory R. Grant; Omar S. Harb; Mark Heiges; Sufen Hu; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; Deborah F. Pinney; Brian Pitts; David S. Roos; Ganesh Srinivasamoorthy; Christian J. Stoeckert; Haiming Wang; Susanne Warrenfeltz

EuPathDB (http://eupathdb.org) resources include 11 databases supporting eukaryotic pathogen genomic and functional genomic data, isolate data and phylogenomics. EuPathDB resources are built using the same infrastructure and provide a sophisticated search strategy system enabling complex interrogations of underlying data. Recent advances in EuPathDB resources include the design and implementation of a new data loading workflow, a new database supporting Piroplasmida (i.e. Babesia and Theileria), the addition of large amounts of new data and data types and the incorporation of new analysis tools. New data include genome sequences and annotation, strand-specific RNA-seq data, splice junction predictions (based on RNA-seq), phosphoproteomic data, high-throughput phenotyping data, single nucleotide polymorphism data based on high-throughput sequencing (HTS) and expression quantitative trait loci data. New analysis tools enable users to search for DNA motifs and define genes based on their genomic colocation, view results from searches graphically (i.e. genes mapped to chromosomes or isolates displayed on a map) and analyze data from columns in result tables (word cloud and histogram summaries of column content). The manuscript herein describes updates to EuPathDB since the previous report published in NAR in 2010.


Nucleic Acids Research | 2011

AmoebaDB and MicrosporidiaDB: functional genomic resources for Amoebozoa and Microsporidia species

Cristina Aurrecoechea; Ana Barreto; John Brestelli; Brian P. Brunk; Elisabet V. Caler; Steve Fischer; Bindu Gajria; Xin Gao; Alan R. Gingle; Gregory R. Grant; Omar S. Harb; Mark Heiges; John Iodice; Jessica C. Kissinger; Eileen Kraemer; Wei Li; Vishal Nayak; Cary Pennington; Deborah F. Pinney; Brian Pitts; David S. Roos; Ganesh Srinivasamoorthy; Christian J. Stoeckert; Charles Treatman; Haiming Wang

AmoebaDB (http://AmoebaDB.org) and MicrosporidiaDB (http://MicrosporidiaDB.org) are new functional genomic databases serving the amoebozoa and microsporidia research communities, respectively. AmoebaDB contains the genomes of three Entamoeba species (E. dispar, E. invadens and E. histolityca) and microarray expression data for E. histolytica. MicrosporidiaDB contains the genomes of Encephalitozoon cuniculi, E. intestinalis and E. bieneusi. The databases belong to the National Institute of Allergy and Infectious Diseases (NIAID) funded EuPathDB (http://EuPathDB.org) Bioinformatics Resource Center family of integrated databases and assume the same architectural and graphical design as other EuPathDB resources such as PlasmoDB and TriTrypDB. Importantly they utilize the graphical strategy builder that affords a database user the ability to ask complex multi-data-type questions with relative ease and versatility. Genomic scale data can be queried based on BLAST searches, annotation keywords and gene ID searches, GO terms, sequence motifs, protein characteristics, phylogenetic relationships and functional data such as transcript (microarray and EST evidence) and protein expression data. Search strategies can be saved within a user’s profile for future retrieval and may also be shared with other researchers using a unique strategy web address.


Nucleic Acids Research | 2017

EuPathDB: the eukaryotic pathogen genomics database resource

Cristina Aurrecoechea; Ana Barreto; Evelina Y. Basenko; John Brestelli; Brian P. Brunk; Shon Cade; Kathryn Crouch; Ryan Doherty; Dave Falke; Steve Fischer; Bindu Gajria; Omar S. Harb; Mark Heiges; Christiane Hertz-Fowler; Sufen Hu; John Iodice; Jessica C. Kissinger; Cris Lawrence; Wei Li; Deborah F. Pinney; Jane A. Pulman; David S. Roos; Achchuthan Shanmugasundram; Fatima Silva-Franco; Sascha Steinbiss; Christian J. Stoeckert; Drew Spruill; Haiming Wang; Susanne Warrenfeltz; Jie Zheng

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a users data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions.


Nucleic Acids Research | 2018

MicrobiomeDB: a systems biology platform for integrating, mining and analyzing microbiome experiments

Francislon S. Oliveira; John Brestelli; Shon Cade; Jie Zheng; John Iodice; Steve Fischer; Cristina Aurrecoechea; Jessica C. Kissinger; Brian P. Brunk; Christian J. Stoeckert; Gabriel da Rocha Fernandes; David S. Roos; Daniel P. Beiting

Abstract MicrobiomeDB (http://microbiomeDB.org) is a data discovery and analysis platform that empowers researchers to fully leverage experimental variables to interrogate microbiome datasets. MicrobiomeDB was developed in collaboration with the Eukaryotic Pathogens Bioinformatics Resource Center (http://EuPathDB.org) and leverages the infrastructure and user interface of EuPathDB, which allows users to construct in silico experiments using an intuitive graphical ‘strategy’ approach. The current release of the database integrates microbial census data with sample details for nearly 14 000 samples originating from human, animal and environmental sources, including over 9000 samples from healthy human subjects in the Human Microbiome Project (http://portal.ihmpdcc.org/). Query results can be statistically analyzed and graphically visualized via interactive web applications launched directly in the browser, providing insight into microbial community diversity and allowing users to identify taxa associated with any experimental covariate.

Collaboration


Dive into the John Iodice's collaboration.

Top Co-Authors

Avatar

Brian P. Brunk

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Steve Fischer

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar

Bindu Gajria

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar

John Brestelli

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Deborah F. Pinney

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge