Gene prediction basically means locating genes along a genome. Also called gene finding, it refers to the process of identifying the regions of genomic DNA that encode genes. This includes protein coding genes, RNA genes and other functional elements such as the regulatory genes.
Helps to annotate large, contiguous sequences
Helps in the identification of fundamental and essential elements of genome such as functional genes, intron, exon, splicing sites, regulatory sites, gene encoding known proteins, motifs, EST, ACR, etc.
Distinguish between coding and non-coding regions of a genome
Predict complete exon intron structures of protein coding regions
Describe individual genes in terms of their function
It has vast application in structural genomics ,functional genomics , metabolomics, transcriptomics, proteomics, genome studies and other genetic related studies including genetics disorders detection, treatment and prevention.
One method is a sequence similarity searches method. It is a conceptually simple approach that is based on finding similarity in gene sequences between ESTs (expressed sequence tags), proteins, or other genomes to the input genome. This approach is based on the assumption that functional regions (exons) are more conserved evolutionarily than nonfunctional regions (intergenic or intronic regions). Once there is similarity between a certain genomic region and an EST, DNA, or protein, the similarity information can be used to infer gene structure or function of that region. Local alignment and global alignment are two methods based on similarity searches. The most common local alignment tool is the BLAST family of programs, which detects sequence similarity to known genes, proteins, or ESTs.
One method is based on gene structure and signal-based searches. It uses gene structure as a template to detect genes. Ab initio gene predictions rely on two types of sequence information: signal sensors and content sensors. Exon detection must rely on the content sensors.
The search by this method thus relies on the major feature present in the genes. Many algorithms are applied for modeling gene structure, such as Dynamic Programming, linear discriminant analysis, Linguist methods, Hidden Markov Model and Neural Network. Based on these models, a great number of ab initio gene prediction programs have been developed. Some of the frequently used ones are;
During analysis, we have to study biologically significant sites include;
Protein binding sites (promotors, histones, etc.)
DNA 3D structure features
Open reading frames
Our company, BioinfoLytics, is affliated with BioCode and is a project, which is covering many topics on Genomics, Proteomics, their analysis using many tools in a cool way, Sequence Alignment & Analysis, Bioinformatics Scripting & Software Development, Phylogenetic and Phylogenomic Analysis, Functional Analysis, Biological Data Analysis & Visualization, Custom Analysis, Biological Database Analysis, Molecular Docking, Protein Structure Prediction and Molecular Dynamics etc for the seekers of Biocode to further develop their interest to take part in these services to fulfill their requirements and obtain their desired results. We are providing such a platform where one can find opportunity to learn, research projects analysis and get help and huge knowledge based on molecular, computational and analytical biology.
We are providing “Gene Prediction” service to our customers to study biologically important features and sites of genes and to strive high quality research and will advance science in the domain of Genome Analysis.