BACKGROUND: A fundamental characteristic of multicellular organisms is the specialization of functional cell types through the process of differentiation. These specialized cell types not only characterize the normal functioning of different organs a...
BACKGROUND: RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep ...
IEEE/ACM transactions on computational biology and bioinformatics
Nov 7, 2017
Disease gene prediction is a challenging task that has a variety of applications such as early diagnosis and drug development. The existing machine learning methods suffer from the imbalanced sample issue because the number of known disease genes (po...
IEEE/ACM transactions on computational biology and bioinformatics
Jul 13, 2017
MicroRNAs (miRNAs) are short non-coding RNAs which bind to mRNAs and regulate their expression. MiRNAs have been found to be associated with initiation and progression of many complex diseases. Investigating miRNAs and their targets can thus help dev...
BACKGROUND: Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristic...
We present GuideScan software for the design of CRISPR guide RNA libraries that can be used to edit coding and noncoding genomic regions. GuideScan produces high-density sets of guide RNAs (gRNAs) for single- and paired-gRNA genome-wide screens. We a...
We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a give...
BACKGROUND: RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recog...
BACKGROUND: The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinfor...
BACKGROUND: High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significa...