Translation initiation site detection software tools | Transcription data analysis
Translation is a key process for gene expression. Timely identification of the translation initiation site (TIS) is very important for conducting in-depth genome analysis. With the avalanche of genome sequences generated in the postgenomic age, it is highly desirable to develop automated methods for rapidly and effectively identifying TIS.
Produces neural network predictions of translation start in vertebrate and Arabidopsis thaliana nucleotide sequences. NetStart has been trained on cDNA-like sequences and will therefore presumably have better performance for cDNAs and ESTs. We have not tested the performance on genome data which may contain introns adjacent to the start codon.
A program for identifying the initiation codons in cDNA sequences. ATGpr can be used to predict whether an initiation codon is present or absent in a piece of cDNA and which ATG is the initiation codon for cases where a codon appears to be present. The method, which uses linear discriminant analysis, has been rigorously tested on a 660 sequence, non-redundant dataset.
A highly accurate predictor for translation initiation sites in human mRNAs. Our algorithm includes two novel ideas. First, we introduce a class of new sequence-similarity kernels based on string editing, called edit kernels, for use with support vector machines (SVMs) in a discriminative approach to predict TISs. The edit kernels are simple and have significant biological and probabilistic interpretations. Although the edit kernels are not positive definite, it is easy to make the kernel matrix positive definite by adjusting the parameters. Second, we convert the region of an input mRNA sequence downstream to a putative TIS into an amino acid sequence before applying SVMs to avoid the high redundancy in the genetic code.
A software tool for improving the results of conventional gene finders for prokaryotic genomes with regard to exact localization of the translation initiation site (TIS). At the current state TICO provides an interface for direct post processing of the predictions obtained from the widely used program GLIMMER. Although the underlying method is not based on any specific assumptions about characteristic sequence features of prokaryotic TIS the prediction rates of our tool are competitive on experimentally verified test data.
Predicts translation initiation site(s) in vertebrate DNA/mRNA/cDNA sequences. TIS Miner was trained on 3,312 vertebrate mRNA sequences. The training accuracy is 92.45% at 80.19% sensitivity and 96.48% specificity.
Performs the internal ribosomal entry site (IRES) secondary structure prediction. VIPS is a software which can evaluate and predict for all four different groups of IRESs. The software integrates RNA secondary structure prediction program, comparison software and pseudoknot program to increase the accuracy rate for IRES elements prediction. It can facilitate users to identify candidate IRES structures from their target sequences.