最近做基因组数据分析多一些，这个是自然，现在可能三五万就可以轻松搞定一个常规基因组（1G以下二倍体），后续可以分析，或者需要分析的内容有很多，可以挖掘的故事也很多。自然而然也开始关注一些相关分析软件。
无意间看到了 GeneMark！
感慨，这个团队太牛~
简单列一下一款软件的30年更新，与大伙共赏。
1993 GeneMark GeneMark: parallel gene recognition for both DNA strands
1998 GeneMark. hmm: new solutions for gene finding
1998 GeneMark-Genesis How to interpret an anonymous bacterial genome: machine learning approach to gene identification.
2001 GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions
2005 GeneMark: web software for gene finding in prokaryotes, eukaryotes and viruses
2014 GeneMark-ET Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm.
2015 GeneMarkS-T Identification of protein coding regions in RNA transcripts
2020 GeneMark-EP and-EP+: automatic eukaryotic gene prediction supported by spliced aligned proteins
2020 GeneMark-EP+: eukaryotic gene prediction with self-training in the space of genes and proteins
2021 GeneMark-HM: improving gene prediction in DNA sequences of human microbiome
2023 GeneMark-ETP: Automatic Gene Finding in Eukaryotic Genomes in Consistence with Extrinsic Data
整理完发表的论文文稿，我发现软件官网也有自己的列表，感兴趣的朋友也可以看看
http://exon.gatech.edu/genemark/references.html
写在最后
有时候，锚定一个事情的人，太强。与大伙共勉~
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