ArticleNucleic acids research2012
IPAVS: Integrated Pathway Resources, Analysis and Visualization System.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- pathDIP 4: an extended pathway annotations and enrichment analysis resource for human, model organisms and domesticated species.Nucleic acids research · 2020Article
- NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families.PloS one · 2020Article
- pathDIP: an annotated resource for known and predicted human gene-pathway associations and pathway enrichment analysis.Nucleic acids research · 2017Article
- Epigenetic profiling of human brain differential DNA methylation networks in schizophrenia.BMC medical genomics · 2016Article
- Principles and practice of lipidomics.Journal of inherited metabolic disease · 2015Review
- Conversion of KEGG metabolic pathways to SBGN maps including automatic layout.BMC bioinformatics · 2013Article
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- Analysis of schizophrenia and hepatocellular carcinoma genetic network with corresponding modularity and pathways: novel insights to the immune system.BMC genomics · 2013Article
- Using biological pathway data with paxtools.PLoS computational biology · 2013Article
- Public domain databases for medicinal chemistry.Journal of medicinal chemistry · 2012Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrated Pathway Resources, Analysis and Visualization System (iPAVS) is an integrated biological pathway database designed to support pathway discovery in the fields of proteomics, transcriptomics, metabolomics and systems biology. The key goal of IPAVS is to provide biologists access to expert-curated pathways from experimental data belonging to specific biological contexts related to cell types, tissues, organs and diseases. IPAVS currently integrates over 500 human pathways (consisting of 24, 574 interactions) that include metabolic-, signaling- and disease-related pathways, drug-action pathways and several large process maps collated from other pathway resources. IPAVS web interface allows biologists to browse and search pathway resources and provides tools for data import, management, visualization and analysis to support the interpretation of biological data in light of cellular processes. Systems Biology Graphical Notations (SBGN) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway notations are used for the visual display of pathway information. The integrated datasets in IPAVS are made available in several standard data formats that can be downloaded. IPAVS is available at: http://ipavs.cidms.org.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.