
Integrative multi-species prediction (IMP) is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at http://imp.princeton.edu.
Internet, VDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470::Genetikk og genomikk: 474, Proteins, Articles, Genomics, VDP::Mathematics and natural science: 400::Basic biosciences: 470::Genetics and genomics: 474, Zebrafish Proteins, Rats, Repressor Proteins, Systems Integration, Mice, VDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425, VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429, Genes, VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Kunnskapsbaserte systemer: 425, Computer Graphics, Animals, Humans, Gene Regulatory Networks, Software, VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering, visualisering, signalbehandling, bildeanalyse: 429
Internet, VDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470::Genetikk og genomikk: 474, Proteins, Articles, Genomics, VDP::Mathematics and natural science: 400::Basic biosciences: 470::Genetics and genomics: 474, Zebrafish Proteins, Rats, Repressor Proteins, Systems Integration, Mice, VDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425, VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429, Genes, VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Kunnskapsbaserte systemer: 425, Computer Graphics, Animals, Humans, Gene Regulatory Networks, Software, VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering, visualisering, signalbehandling, bildeanalyse: 429
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 78 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
