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ECOMICS specifications


Unique identifier OMICS_23108
Alternative name ECosystem trans-OMICS investigation
Software type Toolkit/Suite
Interface Web user interface
Restrictions to use None
Computer skills Basic
Stability Stable
Maintained Yes


  • Bm-Char
  • E-class
  • FT2B
  • HetMap


  • person_outline Jun Kikuchi

Publication for ECosystem trans-OMICS investigation

ECOMICS citations


Predicting potential drug drug interactions on topological and semantic similarity features using statistical learning

PLoS One
PMCID: 5940181
PMID: 29738537
DOI: 10.1371/journal.pone.0196865

[…] e whole network as a list of relations U={⟨u1,u2⟩,⟨u1,u3⟩,…,⟨ui,uj⟩,…,⟨un-1,un⟩}, where n is the number of nodes in the network. Each term of the list comprises a feature vector and a relationship (i.e., class) label. The label is 1 when ui following uj and 0 otherwise. A feature vector is composed by the two feature subsets, as described in the next section.Our basic assumption is that similar no […]


Genome wide analysis of the SPL/miR156 module and its interaction with the AP2/miR172 unit in barley

Sci Rep
PMCID: 5935748
PMID: 29728569
DOI: 10.1038/s41598-018-25349-0

[…] bations. Recently, AS was identified in barley and its possible function was explored by network analysis. FLOWERING LOCUS T (FT) in Brachypodium undergoes age dependent AS and produces two (FT2α and FT2β) splice variants but, only FT2β was found to be involved in the regulation of flowering. Similarly, 16 of 17 HvSPLs undergo AS and generate diverse transcript and protein sequences (Fig. , Table  […]


MIKCC type MADS box genes in Rosa chinensis: the remarkable expansion of ABCDE model genes and their roles in floral organogenesis

PMCID: 5928068
PMID: 29736250
DOI: 10.1038/s41438-018-0031-4

[…] analysis of gene expression in the different whorls of the floral organs of both Old Blush and Viridiflora (Fig. c, d) showed that the regional expression restrictions of the rose A-, B-, C-, D-, and E-class genes in the different whorls of floral organs shifted widely in Viridiflora vs. Old Blush (Fig. ). Specifically, the elevated expression levels of four genes, i.e., RcAG2, RcAG3, RcAG4, and R […]


Alternative polyadenylation drives genome to phenome information detours in the AMPKα1 and AMPKα2 knockout mice

Sci Rep
PMCID: 5915415
PMID: 29691479
DOI: 10.1038/s41598-018-24683-7

[…] ated in AMPKα2 knockout mice. The only down-regulated pathway was regulation of neuron death.Figure 3The 67 up-regulated DE-APSs located in protein coding genes mainly extended from exons to introns (e class code with 52%), followed by i class code with 21% (Fig. ). In contrast, the 15 down-regulated DE-APSs were dominantly located in distal regions −53% assigned to o class code and 40% designated […]


Transcriptomic Analysis of Flower Bud Differentiation in Magnolia sinostellata

PMCID: 5924554
PMID: 29659525
DOI: 10.3390/genes9040212

[…] any aspects of floral development, such as SEP (SEPALLATA), were identified in Arabidopsis sp. and other model plants []. Thus, the ABC model was replaced by the ABCDE model, which states that A- and E-class genes determine the first whorl, the calyx; A-, B- and E-class genes interact to form the petals in the second whorl; B-, C-, and E-class genes interact to regulate the third whorl, the stamen […]


Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature

J Biomed Semantics
PMCID: 5896136
PMID: 29650041
DOI: 10.1186/s13326-018-0181-1

[…] ed by these two OWL annotation properties. Based on the position in the list of retrieved terms, Pilehvar and Collier [] calculated the mean and median rank as well as the percentage of phenotypes (i.e. class names in the HPO) for which the rank was equal to one (i.e. the first term in the list retrieved has a synonym in the HPO). Pilehvar and Collier [] reported improvements by post-processing, i […]


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ECOMICS institution(s)
Plant Science Center, RIKEN, Yokohama, Japan; Graduate School of Nanobioscience, Yokohama City University, Yokohama, Japan; Advanced Science Institute, RIKEN, Wako, Japan; Bioinformatics and Systems Engineering Division, RIKEN, Yokohama, Japan; Biomass Engineering Program, RIKEN Cluster for Innovation, Wako, Japan; Graduate School of Bioagriculture Sciences, Nagoya University, Nagoya, Japan
ECOMICS funding source(s)
Supported, in part, by Grants-in-Aid for Scientific Research for challenging exploratory research, and Scientific Research (A) from the Ministry of Education, Culture, Sports, Science, and Technology, Japan, and, in part, by grants from Research and Development Program for New Bio-industry Initiatives of the Bio-oriented Technology Research Advancement Institution (BRAIN), and the New Energy and Industrial Technology Development Organization (NEDO).

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