An ab initio program for gene finding in bacterial or archaeal genomes. Based on cross validations of 422 prokaryotic genomes, ZCURVE 3.0 has slightly higher accuracy than Glimmer 3.02. As the most prominent advantage, ZCURVE 3.0 can automatically select essential genes from the list of protein-coding genes, whereas none of the other ab initio gene-finding programs can provide such convenience.
A universal approach and tool, based on orthology and phylogeny, to offer gene essentiality annotations. Compared with the essential genes uniquely identified by the lethal screening, the essential genes predicted only by Gepop are associated with more protein-protein interactions, especially in the three bacteria with lower AUC scores (<0.7).
A web app for predicting essential genes of bacteria genome using only sequence compositional features. These features are all derived from the primary sequences, i.e., nucleotide sequences and protein sequences. EGP uses a support vector machine (SVM)-based method to predict essential genes.
Allows users to estimate the number of essential genes in a genome on the basis of data from a random transposon mutagenesis experiment, through the use of a Gibbs sampler. negenes consists of a method for predicting the proportion and identifying essential genes in a genome that is based on the sequence information of a genome.
Aims to facilitate the comprehensive exploration of human essential genes. HEGIAP is a web server that integrates analytical and visualization tools to give a multilevel interpretation of gene essentiality for a single gene. The software supports both feature- and gene-oriented analyses. It provides an overall gene property graph, boxplots for gene properties, histone modification, methylation, and chromatin accessibility profiles, the Hi-C contact map of chromatin structure and offers a drug-screening tool.
Identifies potential drug targets from bacterial proteome. TiD removes paralogous proteins, picks essential ones, and excludes proteins homologous with host organisms. It classifies proposed targets as known, novel and virulent. The tool can identify drug targets from whole proteome in less than two hours. It presents minimum putative targets from whole proteome for downstream target prioritization and experimental validation.