Evidence map›Paper›PMID 17678535›Full record

ArticleBMC bioinformatics2007

PepBank--a database of peptides based on sequence text mining and public peptide data sources.

Timur Shtatland, Daniel Guettler, Misha Kossodo, Misha Pivovarov, Ralph Weissleder

Abstract read
In one paragraph

Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

66 citing papers in PubMed.

  1. Bioactive Peptides From theFood science & nutrition · 2026
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  16. Can the SARS-CoV-2 Spike Protein Bind Integrins Independent of the RGD Sequence?Frontiers in cellular and infection microbiology · 2021
    Article
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  18. Article
  19. DPL: a comprehensive database on sequences, structures, sources and functions of peptide ligands.Database : the journal of biological databases and curation · 2020
    Article
  20. Review

6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Timur ShtatlandCenter for Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Bldg, 149, 13th Street, Room 5406, Charlestown, MA 02129, USA. tshtatland@partners.org
Daniel Guettler
Misha Kossodo
Misha Pivovarov
Ralph Weissleder

Funding

StatisticsP50CA086355 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI WEISSLEDER, MD, PHD, RALPH · 2000 to 2015
$27.8M
Visualzing Lymphocyte Attack on Pancreas B CellsP01AI054904 · NIAID · JOSLIN DIABETES CENTER · PI MATHIS, DIANE J · 2003 to 2013
$16.0M
Tumor-Stroma Interacions in the Tumor MicroenvironmentU54CA126515 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HYNES, RICHARD O · 2006 to 2010
$6.5M
NCI NIH HHS P50 CA086355NCI NIH HHS P50-CA86355NCI NIH HHS U54 CA126515NCI NIH HHS U54-CA126515NIAID NIH HHS P01 AI054904NIAID NIH HHS P01-AI54904
6 · The paper itself

Abstract

backgroundPeptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources. DESCRIPTION: We have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery.

conclusionWe have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on http://pepbank.mgh.harvard.edu/, and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (http://www.cpan.org/).

Indexed as

Database Management SystemsDatabases, ProteinInternetNatural Language ProcessingUser-Computer InterfaceAmino Acid SequenceInformation Storage and RetrievalMolecular Sequence DataPeptidesPeriodicals as TopicSequence Analysis, ProteinPeptides

Identifiers

PMID17678535
PMCPMC1976427

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.