KaPPA-View4: a metabolic pathway database for representation and analysis of correlation networks of gene co-expression and metabolite co-accumulation and omics data.
Sakurai. Nozomu N; Ara. Takeshi T; Ogata. Yoshiyuki Y; Sano. Ryosuke R; Ohno. Takashi T; Sugiyama. Kenjiro K; Hiruta. Atsushi A; Yamazaki. Kiyoshi K; Yano. Kentaro K; Aoki. Koh K; Aharoni. Asaph A; Hamada. Kazuki K; Yokoyama. Koji K; Kawamura. Shingo S; Otsuka. Hirofumi H; Tokimatsu. Toshiaki T; Kanehisa. Minoru M; Suzuki. Hideyuki H; Saito. Kazuki K; Shibata. Daisuke D
Key Findings
- It overlays correlation networks onto KEGG pathway maps for up to four pathways at once
- It includes co‑expression data from several public databases for multiple species (human, mouse, rat, plants)
- It aims to help discover new gene functions or regulatory links by visual inspection
Practical Outcomes
- For most biohackers, the tool offers little direct, actionable guidance for diet, supplements, or training. Only users who can generate their own transcriptome or metabolome data and have bioinformatics skills might use it to explore metabolic mechanisms, which is beyond typical DIY health experiments.
Summary
KaPPA-View4 is a web‑based database that lets scientists draw gene‑to‑gene and metabolite‑to‑metabolite correlation lines on metabolic pathway maps. It’s a research‑tool for visualizing big‑data patterns, not a health supplement or protocol you can take or follow.
Abstract
Correlations of gene-to-gene co-expression and metabolite-to-metabolite co-accumulation calculated from large amounts of transcriptome and metabolome data are useful for uncovering unknown functions of genes, functional diversities of gene family members and regulatory mechanisms of metabolic pathway flows. Many databases and tools are available to interpret quantitative transcriptome and metabolome data, but there are only limited ones that connect correlation data to biological knowledge and can be utilized to find biological significance of it. We report here a new metabolic pathway database, KaPPA-View4 (http://kpv.kazusa.or.jp/kpv4/), which is able to overlay gene-to-gene and/or metabolite-to-metabolite relationships as curves on a metabolic pathway map, or on a combination of up to four maps. This representation would help to discover, for example, novel functions of a transcription factor that regulates genes on a metabolic pathway. Pathway maps of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and maps generated from their gene classifications are available at KaPPA-View4 KEGG version (http://kpv.kazusa.or.jp/kpv4-kegg/). At present, gene co-expression data from the databases ATTED-II, COXPRESdb, CoP and MiBASE for human, mouse, rat, Arabidopsis, rice, tomato and other plants are available.
Study Information
pubmed
2010
2010-11-19T00:00:00.000Z
10.1093/nar/gkq989
72
36