1.
ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank.
Chen, J, Guo, M, Li, S, Liu, B
Bioinformatics (Oxford, England). 2017;(21):3473-3476
Abstract
SUMMARY As one of the most important tasks in protein sequence analysis, protein remote homology detection is critical for both basic research and practical applications. Here, we present an effective web server for protein remote homology detection called ProtDec-LTR2.0 by combining ProtDec-Learning to Rank (LTR) and pseudo protein representation. Experimental results showed that the detection performance is obviously improved. The web server provides a user-friendly interface to explore the sequence and structure information of candidate proteins and find their conserved domains by launching a multiple sequence alignment tool. AVAILABILITY AND IMPLEMENTATION The web server is free and open to all users with no login requirement at http://bioinformatics.hitsz.edu.cn/ProtDec-LTR2.0/. CONTACT bliu@hit.edu.cn.
2.
CoSpliceNet: a framework for co-splicing network inference from transcriptomics data.
Aghamirzaie, D, Collakova, E, Li, S, Grene, R
BMC genomics. 2016;(1):845
Abstract
BACKGROUND Alternative splicing has been proposed to increase transcript diversity and protein plasticity in eukaryotic organisms, but the extent to which this is the case is currently unclear, especially with regard to the diversification of molecular function. Eukaryotic splicing involves complex interactions of splicing factors and their targets. Inference of co-splicing networks capturing these types of interactions is important for understanding this crucial, highly regulated post-transcriptional process at the systems level. RESULTS First, several transcript and protein attributes, including coding potential of transcripts and differences in functional domains of proteins, were compared between splice variants and protein isoforms to assess transcript and protein diversity in a biological system. Alternative splicing was shown to increase transcript and function-related protein diversity in developing Arabidopsis embryos. Second, CoSpliceNet, which integrates co-expression and motif discovery at splicing regulatory regions to infer co-splicing networks, was developed. CoSpliceNet was applied to temporal RNA sequencing data to identify candidate regulators of splicing events and predict RNA-binding motifs, some of which are supported by prior experimental evidence. Analysis of inferred splicing factor targets revealed an unexpected role for the unfolded protein response in embryo development. CONCLUSIONS The methods presented here can be used in any biological system to assess transcript diversity and protein plasticity and to predict candidate regulators, their targets, and RNA-binding motifs for splicing factors. CoSpliceNet is freely available at http://delasa.github.io/co-spliceNet/ .