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We have then validated the extracted modules by integrating the annotation of known MIPS complexes, GO categories and pathways.
In this review, we focus on computational methods of inferring miRNA functions, including miRNA functional annotation and inferring miRNA regulatory modules, by integrating heterogeneous data sources.
The above methods (Table 3) aim at exploring general miRNA mRNA regulatory modules by integrating miRNA-target prediction on sequence with expression profiles of miRNA and mRNA or other data sources.
Le et al. [ 60] developed the regression-based model called PIMiM (Protein Interaction-based MicroRNA Modules) to predict miRNA-regulated modules by integrating expression profiles of both miRNAs and genes, sequence-based predictions of miRNA-mRNA interactions and protein-protein interactions data.
These include works that detect functional modules by integrating phenotypic and physical data (Ideker et al., 2002; Nariai et al., 2004; Peleg et al., 2010) or that reconstruct or annotate signaling pathways or binding events (Gao et al., 2004; Ourfali et al., 2007; Yeang et al., 2004; Yeger-Lotem et al., 2009).
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In this study, the mineral model was built in the Interactive Petrophysics (IP's) Mineral Solver module by integrating all regional sedimentological, petrographic, SEM (Scanning electronic microscope), pulse decay and X-ray diffraction data (XRD) from core and chip cutting samples.
Progressive testing of the system starts with the lowest level of software module, followed by integrating modules, and working up to testing the complete safety system.
Motivation: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data.
Li et al. (2014) proposed a novel method called Mirsynergy to detect miRNA regulatory modules (MiRMs) by integrating mRNA/miRNA expression profiles, target site information and gene-gene interaction to form MiRMs, which can automatically determine the module number and improve the time complexity [ 17].
Our gene modules were generated by integrating multiple large scale evidence of gene function categorizations such as protein-protein interaction networks, gene annotation databases, and microRNA target genes.
The identification of the significant expression changed functional modules was conducted by integrating mRNA expression, protein-protein interaction and Gene Ontology (GO) function annotation.
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models by integrating
components by integrating
platforms by integrating
nodes by integrating
packages by integrating
elements by integrating
samples by integrating
mode by integrating
modules by determining
modules by importing
modules by tracing
modules by developing
modules by undervaluing
modules by examining
modules by letting
modules by noting
modules by introducing
modules by performing
modules by inducing
modules by controlling
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