StopKB: a comprehensive knowledgebase for nonsense suppression therapies.

Nonsense variations, characterized by premature termination codons, play a major role in human genetic diseases as well as in cancer susceptibility. Despite their high prevalence, effective therapeutic strategies targeting premature termination codons remain a challenge. To understand and explore the intricate mechanisms involved, we developed StopKB, a comprehensive knowledgebase aggregating data from multiple sources on nonsense variations, associated genes, diseases, and phenotypes.

Characterization of accessory genes in coronavirus genomes.

Background: The Covid19 infection is caused by the SARS-CoV-2 virus, a novel member of the coronavirus (CoV) family. CoV genomes code for a ORF1a / ORF1ab polyprotein and four structural proteins widely studied as major drug targets. The genomes also contain a variable number of open reading frames (ORFs) coding for accessory proteins that are not essential for virus replication, but appear to have a role in pathogenesis.

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

Background: The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis.

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of 'meta-methods' that systematically run several aligners and merge the output into one single solution.

Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis.

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers.

vALId: validation of protein sequence quality based on multiple alignment data.

The validation of sequences is essential to perform accurate phylogeny and structure/function analysis. However among the thousands of protein sequences available in the public databases, most have been predicted in silico and have not systematically undergone a quality verification. It has recently become evident that they often contain sequence errors.