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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 ...
NodeXL is intended for users with little or no programming experience to allow them to collect, analyze, and visualize a variety of networks. [10] NodeXL integrates into Microsoft Excel 2007, 2010, 2013, 2016, 2019 and 365 and opens as a workbook with a variety of worksheets containing the elements of a graph structure such as edges and nodes.
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.
Program to recognize vertebrate RNA polymerase II promoters: Vertebrates [7] EasyGene: The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Prokaryotes [8] [9] EuGene: Integrative gene finding: Prokaryotes, Eukaryotes [10] [11] FGENESH: HMM-based gene structure prediction: multiple genes ...
PAFit can analyse the evolution of complex networks by estimating preferential attachment and node fitness; tnet performs analysis of weighted networks, two-mode networks, and longitudinal networks; ergm is a set of tools to analyze and simulate networks based on exponential random graph models exponential random graph models;
MAFFT – The first version, created by Kazutaka Katoh in 2002, used an algorithm based on progressive alignment, in which the sequences were clustered with the help of the fast Fourier transform. [2] MAFFT v5 – The second generation software, released in 2005, was a rewrite of the original software. [3]
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.
Generic Feature Format Version 3 Genome Variation Format , with additional pragmas and attributes for sequence_alteration features GFF2/GTF had a number of deficiencies, notably that it can only represent two-level feature hierarchies and thus cannot handle the three-level hierarchy of gene → transcript → exon.