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GeneMark is a generic name for a family of ab initio gene prediction algorithms and software programs developed at the Georgia Institute of Technology in Atlanta.Developed in 1993, original GeneMark was used in 1995 as a primary gene prediction tool for annotation of the first completely sequenced bacterial genome of Haemophilus influenzae, and in 1996 for the first archaeal genome of ...
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.
[2] ATGpr: Identifies translational initiation sites in cDNA sequences: Human [3] Prodigal: Its name stands for Prokaryotic Dynamic Programming Genefinding Algorithm. It is based on log-likelihood functions and does not use Hidden or Interpolated Markov Models. Prokaryotes, Metagenomes (metaProdigal) [4] AUGUSTUS: Eukaryote gene predictor ...
In molecular biology and genetics, DNA annotation or genome annotation is the process of describing the structure and function of the components of a genome, [2] by analyzing and interpreting them in order to extract their biological significance and understand the biological processes in which they participate. [3]
In bioinformatics, MAFFT (multiple alignment using fast Fourier transform) is a program used to create multiple sequence alignments of amino acid or nucleotide sequences. . Published in 2002, the first version used an algorithm based on progressive alignment, in which the sequences were clustered with the help of the fast Fourier transfo
Irrespective of the problem category, the process of solving a problem can be divided into two broad steps: constructing an efficient algorithm, and implementing the algorithm in a suitable programming language (the set of programming languages allowed varies from contest to contest). These are the two most commonly tested skills in programming ...
Second Version of GLIMMER i.e., GLIMMER 2.0 was released in 1999 and it was published in the paper Improved microbial identification with GLIMMER. [4] This paper [4] provides significant technical improvements such as using interpolated context model instead of interpolated Markov model and resolving overlapping genes which improves the accuracy of GLIMMER.
Techniques from evolutionary algorithms applied to the modeling of biological evolution are generally limited to explorations of microevolutionary processes and planning models based upon cellular processes. In most real applications of EAs, computational complexity is a prohibiting factor. [3]