Selecting high-quality negative samples for effectively predicting protein-RNA interactions
نویسندگان
چکیده
منابع مشابه
Selecting against accidental RNA interactions
Random base-pairing interactions between messenger RNAs and noncoding RNAs can reduce translation efficiency.
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Protein-protein interactions PPIs play a crucial role in cellular processes. In the present work, a new approach is proposed to construct a PPI predictor training a support vector machine model through a mutual information filter-wrapper parallel feature selection algorithm and an iterative and hierarchical clustering to select a relevance negative training set. By means of a selected suboptimu...
متن کاملHigh-throughput characterization of protein–RNA interactions
RNA-binding proteins (RBPs) are important regulators of eukaryotic gene expression. Genomes typically encode dozens to hundreds of proteins containing RNA-binding domains, which collectively recognize diverse RNA sequences and structures. Recent advances in high-throughput methods for assaying the targets of RBPs in vitro and in vivo allow large-scale derivation of RNA-binding motifs as well as...
متن کاملKernel methods for predicting protein-protein interactions
MOTIVATION Despite advances in high-throughput methods for discovering protein-protein interactions, the interaction networks of even well-studied model organisms are sketchy at best, highlighting the continued need for computational methods to help direct experimentalists in the search for novel interactions. RESULTS We present a kernel method for predicting protein-protein interactions usin...
متن کاملComputational methods for predicting protein-protein interactions.
Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational t...
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ژورنال
عنوان ژورنال: BMC Systems Biology
سال: 2017
ISSN: 1752-0509
DOI: 10.1186/s12918-017-0390-8