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Dive into the research topics where Kim D. Pruitt is active.

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Nucleic Acids Research | 2004

Entrez Gene: gene-centered information at NCBI

Donna Maglott; James Ostell; Kim D. Pruitt; Tatiana Tatusova

Entrez Gene () is NCBIs database for gene-specific information. Entrez Gene includes records from genomes that have been completely sequenced, that have an active research community to contribute gene-specific information or that are scheduled for intense sequence analysis. The content of Entrez Gene represents the result of both curation and automated integration of data from NCBIs Reference Sequence project (RefSeq), from collaborating model organism databases and from other databases within NCBI. Records in Entrez Gene are assigned unique, stable and tracked integers as identifiers. The content (nomenclature, map location, gene products and their attributes, markers, phenotypes and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases) is provided via interactive browsing through NCBIs Entrez system, via NCBIs Entrez programing utilities (E-Utilities), and for bulk transfer by ftp.


Nucleic Acids Research | 2012

NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy

Kim D. Pruitt; Tatiana Tatusova; Garth Brown; Donna Maglott

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of genomic, transcript and protein sequence records. These records are selected and curated from public sequence archives and represent a significant reduction in redundancy compared to the volume of data archived by the International Nucleotide Sequence Database Collaboration. The database includes over 16 000 organisms, 2.4 × 106 genomic records, 13 × 106 proteins and 2 × 106 RNA records spanning prokaryotes, eukaryotes and viruses (RefSeq release 49, September 2011). The RefSeq database is maintained by a combined approach of automated analyses, collaboration and manual curation to generate an up-to-date representation of the sequence, its features, names and cross-links to related sources of information. We report here on recent growth, the status of curating the human RefSeq data set, more extensive feature annotation and current policy for eukaryotic genome annotation via the NCBI annotation pipeline. More information about the resource is available online (see http://www.ncbi.nlm.nih.gov/RefSeq/).


Nucleic Acids Research | 2009

NCBI Reference Sequences: current status, policy and new initiatives.

Kim D. Pruitt; Tatiana Tatusova; William Klimke; Donna Maglott

NCBIs Reference Sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) is a curated non-redundant collection of sequences representing genomes, transcripts and proteins. RefSeq records integrate information from multiple sources and represent a current description of the sequence, the gene and sequence features. The database includes over 5300 organisms spanning prokaryotes, eukaryotes and viruses, with records for more than 5.5 × 106 proteins (RefSeq release 30). Feature annotation is applied by a combination of curation, collaboration, propagation from other sources and computation. We report here on the recent growth of the database, recent changes to feature annotations and record types for eukaryotic (primarily vertebrate) species and policies regarding species inclusion and genome annotation. In addition, we introduce RefSeqGene, a new initiative to support reporting variation data on a stable genomic coordinate system.


Nucleic Acids Research | 2014

RefSeq: an update on mammalian reference sequences

Kim D. Pruitt; Garth Brown; Susan M. Hiatt; Françoise Thibaud-Nissen; Alexander Astashyn; Olga Ermolaeva; Catherine M. Farrell; Jennifer Hart; Melissa J. Landrum; Kelly M. McGarvey; Michael R. Murphy; Nuala A. O’Leary; Shashikant Pujar; Bhanu Rajput; Sanjida H. Rangwala; Lillian D. Riddick; Andrei Shkeda; Hanzhen Sun; Pamela Tamez; Raymond E. Tully; Craig Wallin; David Webb; Janet Weber; Wendy Wu; Michael DiCuccio; Paul Kitts; Donna Maglott; Terence Murphy; James Ostell

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of annotated genomic, transcript and protein sequence records derived from data in public sequence archives and from computation, curation and collaboration (http://www.ncbi.nlm.nih.gov/refseq/). We report here on growth of the mammalian and human subsets, changes to NCBI’s eukaryotic annotation pipeline and modifications affecting transcript and protein records. Recent changes to NCBI’s eukaryotic genome annotation pipeline provide higher throughput, and the addition of RNAseq data to the pipeline results in a significant expansion of the number of transcripts and novel exons annotated on mammalian RefSeq genomes. Recent annotation changes include reporting supporting evidence for transcript records, modification of exon feature annotation and the addition of a structured report of gene and sequence attributes of biological interest. We also describe a revised protein annotation policy for alternatively spliced transcripts with more divergent predicted proteins and we summarize the current status of the RefSeqGene project.


Nucleic Acids Research | 2016

Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

Nuala A. O'Leary; Mathew W. Wright; J. Rodney Brister; Stacy Ciufo; Diana Haddad; Richard McVeigh; Bhanu Rajput; Barbara Robbertse; Brian Smith-White; Danso Ako-adjei; Alexander Astashyn; Azat Badretdin; Yiming Bao; Olga Blinkova; Vyacheslav Brover; Vyacheslav Chetvernin; Jinna Choi; Eric Cox; Olga Ermolaeva; Catherine M. Farrell; Tamara Goldfarb; Tripti Gupta; Daniel H. Haft; Eneida Hatcher; Wratko Hlavina; Vinita Joardar; Vamsi K. Kodali; Wenjun Li; Donna Maglott; Patrick Masterson

The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55 000 organisms (>4800 viruses, >40 000 prokaryotes and >10 000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.


Genome Research | 2009

The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes

Kim D. Pruitt; Jennifer Harrow; Rachel A. Harte; Craig Wallin; Mark Diekhans; Donna Maglott; Steve Searle; Catherine M. Farrell; Jane Loveland; Barbara J. Ruef; Elizabeth Hart; Marie-Marthe Suner; Melissa J. Landrum; Bronwen Aken; Sarah Ayling; Robert Baertsch; Julio Fernandez-Banet; Joshua L. Cherry; Val Curwen; Michael DiCuccio; Manolis Kellis; Jennifer M. Lee; Michael F. Lin; Michael Schuster; Andrew Shkeda; Clara Amid; Garth Brown; Oksana Dukhanina; Adam Frankish; Jennifer Hart

Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.


Nucleic Acids Research | 2016

NCBI prokaryotic genome annotation pipeline.

Tatiana Tatusova; Michael DiCuccio; Azat Badretdin; Vyacheslav Chetvernin; Eric P. Nawrocki; Leonid Zaslavsky; Alexandre Lomsadze; Kim D. Pruitt; Mark Borodovsky; James Ostell

Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBIs Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.


Nature Genetics | 1998

Data management and analysis for gene expression arrays

Olga Ermolaeva; Mohit Rastogi; Kim D. Pruitt; Gregory D. Schuler; Michael L. Bittner; Yidong Chen; Richard Simon; Paul S. Meltzer; Jeffrey M. Trent; Mark S. Boguski

Microarray technology makes it possible to simultaneously study the expression of thousands of genes during a single experiment. We have developed an information system, ArrayDB, to manage and analyse large-scale expression data. The underlying relational database was designed to allow flexibility in the nature and structure of data input and also in the generation of standard or customized reports through a web-browser interface. ArrayDB provides varied options for data retrieval and analysis tools that should facilitate the interpretation of complex hybridization results. A sampling of ArrayDB storage, retrieval and analysis capabilities is available (http://www.nhgri.nih.gov/DIR/LCG/15K/HTML/), along with information on a set of approximately 15,000 genes used to fabricate several widely used microarrays. Information stored in ArrayDB is used to provide integrated gene expression reports by linking array target sequences with NCBIs Entrez retrieval system, UniGene and KEGG pathway views. The integration of external information resources is essential in interpreting intrinsic patterns and relationships in large-scale gene expression data.


Trends in Genetics | 2000

Introducing RefSeq and LocusLink: curated human genome resources at the NCBI

Kim D. Pruitt; Kenneth S. Katz; Hugues Sicotte; Donna Maglott

RefSeq records are included in the Entrez retrieval system (http://www.ncbi.nlm.nih.gov/entrez/). This allows a third query pathway, namely directly by Entrez nucleotide or protein text queries or indirectly by neighboring strategies. LocusLink and RefSeq data are also provided without restriction for ftp transfer (ftp://ncbi.nlm.nih.gov/refseq). Therefore, the combination of LocusLink and RefSeq resources provides a powerful approach to answering such questions as: •Is my sequence from a known gene? (Try blast and look for a RefSeq result.)•What sequence can I use as a standard for gene A? (Try blast or LocusLink.)•Where can I get more information about gene B? (Start at LocusLink.)•What genes are related to disorder Z? (Start at OMIM or LocusLink.)The goal of LocusLink and RefSeq is to include all known genes and their major products. As of the end of August 1999, ∼10 690 loci have been included, 7500 with at least some sequence data and 5985 reference mRNAs. Expanding the LocusLink and RefSeq datasets is an ongoing effort – LocusIDs are established as additional genes are identified, and RefSeq records are added as new links between genes and sequences with complete coding regions are made. The public sites are refreshed weekly. We welcome collaborations with the scientific community to ensure that these resources are as comprehensive and accurate as possible.


Nucleic Acids Research | 2009

Human immunodeficiency virus type 1, human protein interaction database at NCBI

William Fu; Brigitte E. Sanders-Beer; Kenneth S. Katz; Donna Maglott; Kim D. Pruitt; Roger G. Ptak

The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions, was created to catalog all interactions between HIV-1 and human proteins published in the peer-reviewed literature. The database serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. To facilitate this discovery approach, the following information for each HIV-1 human protein interaction is provided and can be retrieved without restriction by web-based downloads and ftp protocols: Reference Sequence (RefSeq) protein accession numbers, Entrez Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. Currently, 2589 unique HIV-1 to human protein interactions and 5135 brief descriptions of the interactions, with a total of 14 312 PMID references to the original articles reporting the interactions, are stored in this growing database. In addition, all protein–protein interactions documented in the database are integrated into Entrez Gene records and listed in the ‘HIV-1 protein interactions’ section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

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Tatiana Tatusova

National Institutes of Health

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Donna Maglott

National Institutes of Health

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Terence Murphy

National Institutes of Health

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Garth Brown

National Institutes of Health

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Craig Wallin

University of California

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Mike Murphy

National Institutes of Health

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Karen Clark

National Institutes of Health

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Ilene Mizrachi

National Institutes of Health

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Catherine M. Farrell

National Institutes of Health

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