Subcellular localization is a key functional characteristic of proteins. A fully automatic and reliable prediction system for protein subcellular needed, especially the analysis large-scale genome sequences.In this paper, Support Vector Machine has been introduced to predict proteins from their amino acid compositions. The total accuracies reach 91.4% three locations in prokaryotic organisms 79.4% four eukaryotic organisms. Predictions by our approach are robust errors N-terminal sequences....

Abstract A high‐performance method was developed for protein secondary structure prediction based on the dual‐layer support vector machine (SVM) and position‐specific scoring matrices (PSSMs). SVM is a new learning technology that has been successfully applied in solving problems field of bioinformatics. The SVM's performance usually better than traditional approaches. further improved by combining PSSM profiles with analysis. PSSMs were generated from PSI‐BLAST profiles, which contain...

Abstract Summary: Large numbers of long intergenic non-coding RNA (lincRNA) have been detected through high-throughput sequencing technology. However, currently we still know very little about their functions. Therefore, a lincRNA function annotation database is needed to facilitate the study in this field. In article, present Linc2GO, web resource that aims provide comprehensive functional annotations for human lincRNA. MicroRNA-mRNA and microRNA-lincRNA interaction data were integrated...

Systems biology efforts are increasingly adopting quantitative, mechanistic modeling to study cellular signal transduction pathways and other networks. However, it is uncertain whether the particular set of kinetic parameter values model closely approximates corresponding biological system. We propose that parameters be assigned statistical distributions reflect degree uncertainty for a comprehensive simulation analysis. From this analysis, we globally identify key components steps in...

Abstract Background Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics plasticity. Although numerous experimental studies have performed to explore the molecular mechanisms underlying palmitoylation processes, intrinsic feature of substrate specificity remained elusive. Thus, computational approaches for prediction are much desirable further design. Results In this work, we present NBA-Palm, a novel method based...

The first web server that provides a user-friendly tool for the prediction and query of <italic>A. thaliana</italic> mRNA m⁶A sites.

N6-Methyladenosine (m6A) is the most common mRNA modification; it occurs in a wide range of taxon and associated with many key biological processes. High-throughput experiments have identified m6A-peaks sites across transcriptome, but studies m6A at transcriptome-wide scale are limited to few species tissue types. Therefore, computational prediction has become an important strategy. In this study, we integrated multiple features (flanking sequences, local secondary structure information,...

Abstract Background Subcellular localization information is one of the key features to protein function research. Locating a specific subcellular compartment essential for efficiently. Proteins which have multiple localizations will provide more clues. This kind proteins may take high proportion, even than 35%. Description We developed database with localizations, designated DBMLoc. The initial release contains 10470 localization-annotated entries. Annotations are collected from primary...

Quantitative prediction of protein-protein binding affinity is essential for understanding interactions. In this article, an atomic level potential mean force (PMF) considering volume correction presented the affinity. The obtained by statistically analyzing X-ray structures complexes in Protein Data Bank. This approach circumvents complicated steps process and very easy to implement practice. It can obtain more reasonable pair compared with traditional PMF shows a classic picture nonbonded...

Abstract Background Cide family proteins including Cidea, Cideb and Cidec/Fsp27, contain an N-terminal CIDE-N domain that shares sequence similarity to the CAD (NCD) of DNA fragmentation factors Dffa/Dff45/ICAD Dffb/Dff40/CAD, a unique C-terminal CIDE-C domain. We have previously shown are newly emerged regulators closely associated with development metabolic diseases such as obesity, diabetes liver steatosis. They modulate many processes lipolysis, thermogenesis TAG storage in brown adipose...

Computational identification of transcription factor binding sites is an important research area computational biology. Positional weight matrix (PWM) a model to describe the sequence pattern sites. Usually, prediction methods based on PWMs require user‐defined thresholds. The arbitrary threshold and also relatively low specificity algorithm prevent result such analysis from being properly interpreted. In this study, method was developed identify over‐represented cis‐elements with PWM‐based...

We uncovered the underlying energy landscape for a cellular network. discovered that of yeast cell-cycle network is funneled towards global minimum (G0/G1 phase) from experimentally measured or inferred inherent chemical reaction rates. The quite robust against random perturbations. This naturally explains robustness physical point view. ratio slope versus roughness becomes quantitative measure can be seen as possible realization Darwinian principle natural selection at level. It provides an...

In an effort to identify genes related the cell line chemosensitivity and evaluate functional relationships between anticancer drugs acting by same mechanism, a supervised machine learning approach called support vector was used label into any of five predefined drug mechanistic categories. Among dozens unequivocally categorized genes, many were known be causally mechanisms. For example, few found involved in biological process triggered (e.g. DNA polymerase epsilon direct target for from...

In this work we have developed a new framework for microarray gene expression data analysis. This is based on hidden Markov models. We benchmarked the performance of probability model-based clustering algorithm several datasets which external evaluation criteria were available. The results showed that approach could produce clusters quality comparable to two prevalent algorithms, but with major advantage determining number clusters. also applied analyze published yeast cell cycle and found...

Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability large scale protein-protein interaction sets makes it possible to develop new function prediction methods based on (PPI) networks. Although several existing combine multiple information resources, is no study that integrates protein domain and PPI networks predict functions. Results context similarity can be a useful index...

Inflammasomes are cytosolic sensors of pathogens. Their activation can lead to the induction caspase-1-mediated inflammatory responses and release several proinflammatory cytokines, including IL-1β. There is a complex relationship between viral infection nucleotide-binding oligomerization domain-like receptors family pyrin domain-containing 3 (NLRP3) inflammasome. The NLRP3 inflammasome essential for antiviral immunity, while excessive may inflammation pathological damage. Meanwhile, viruses...