网站综合信息 www.biodm.com
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- BioDM: Biological Data Mining - The Me
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- BioDM(Biological Data Mining) is a website to make the biological data searching and analyzing much
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- 域名年龄:15年23天 注册日期:2010年06月24日 到期时间:2018年06月24日
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地址:美国 华盛顿州西雅图市亚马逊公司数据中心
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biodm.com
域名年龄: 15年23天注册时间: 2010-06-24
到期时间: 2018-06-24
注 册 商: CHENGDU FLY-DIGITAL TECHNOLOGY CO., LTD
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联系电话: +86.02868399778
获取时间: 2016年09月23日 10:09:37
Domain Name: BIODM.COM
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Sponsoring Registrar IANA ID: 1605
Whois Server: whois.sudu.cn
Referral URL: http://www.sudu.cn
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Updated Date: 2016-08-19
Creation Date: 2010-06-24
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Domain Name: BIODM.COM
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Updated Date: 2016-08-19T17:07:01Z
Creation Date: 2010-06-24T23:36:09Z
Registrar Registration Expiration Date: 2018-06-24T23:36:09Z
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Registry Registrant ID:
Registrant Name: gangcai xie
Registrant Organization: gangcai xie
Registrant Street: shang hai shi yue yang lu 320 hao sheng li lou 363 shi
Registrant City: shanghai
Registrant State/Province: shanghai
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Registrant Country: china
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Tech Postal Code: 200031
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网站头文件(HTTP Header)
HTTP/1.1 200 OK 服务器:nginx/1.2.1 访问时间:2013年08月25日 15:29:39 类型:text/html; charset=UTF-8 Transfer-Encoding: chunked 连接:keep-alive Keep-Alive: timeout=20 动作:Accept-Encoding 语言环境:PHP/5.2.9 X-Pingback: http://www.biodm.com/xmlrpc.php Content-Encoding: gzip 网站编码:UTF-8
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抓取时间:2015年10月25日 19:26:50
网址:http://www.biodm.com/
标题:BioDM: Biological Data Mining - The Meaning Of Big BioData
关键字:
描述:BioDM(Biological Data Mining) is a website to make the biological data searching and analyzing much easier.
主体:
网址:http://www.biodm.com/
标题:BioDM: Biological Data Mining - The Meaning Of Big BioData
关键字:
描述:BioDM(Biological Data Mining) is a website to make the biological data searching and analyzing much easier.
主体:
Biological Data MiningHomePageBioDataBioDigBioGraphicsGenomeFactsBioDrugBioQuestionsAboutBioDig: Finding Homologous GenesPublished on September 21, 2012,by gangcai in BioDig.1. NCBI HomoloGenelink: http://www.ncbi.nlm.nih.gov/HomoloGene/HTML/homologene_buildproc.htmlProteins from input organisms-> bastp-> find DNA sequence of proteins -> synteny -> maximaization global score2. Online blog 1link: http://www.personal.psu.edu/zuz17/blogs/psu_life/2011/02/understand-ucsc-netchain-alignment-1.html3. paper1link: http://genome.cshlp.org/content/11/5/803.full“Computational Inference of Homologous Gene Structures in the Human Genome”4. paper2link: http://www.sciencemag.org/content/320/5875/486.full”Eukaryotic genomes differ in the degree to which genes remain on corresponding chromosomes (synteny) and in corresponding orders (collinearity) over time (1). For example, most eutherian (placental mammal) orders have incurred only moderate reshuffling of chromosomal segments since descent from common ancestors ∼130 million years ago (2). Indeed, karyotype evolution along major vertebrate lineages appears to have been slow since an inferred whole-genome duplication occurred ∼500 million years ago (3). Accordingly, accurate identification of orthologs across eutherian taxa is relatively routine, and deduction of synteny and collinearity is often straightforward with best-in-genome criteria (4), identifying one-to-one best matching chromosomal regions in pairwise genome comparisons.”5. Through evolutionary analysislink: http://genome.cshlp.org/content/8/3/163.full6. Ensembl Gene Homolog prediction methodlink: http://www.ensembl.org/info/docs/compara/homology_method.html”http://www.ensembl.org/info/website/news.htmlProteinTrees and homologies (all species)GeneTrees (protein-coding) with new/updated genebuilds and assembliesClustering using hcluster_sgMultiple sequence alignments using MCoffee or MafftPhylogenetic reconstruction using TreeBeSTHomology inferencePairwise gene-based dN/dS scores for high coverage species pairs only (both on orthologues and paralogues)GeneTree stable ID mappingPer family gene dynamics using CAFEncRNAtrees and homologies (all species)Classification based on Rfam modelsMultiple sequence alignments with InfernalPhylogenetic reconstruction using RAxMLPhylogenetic reconstruction using FastTree2 and RAxML-Light for very big familiesAdditional multiple sequence alignments with Prank (w/ genomic flanks)Additional phylogenetic reconstruction using PhyML and NJPhylogenetic tree merging using TreeBeSTPer family gene dynamics using CAFEHomology inference”7. UCSC(chimpanzee as example)“The RNAs were aligned against the chimp genome using blat; those with an alignment of less than 15% were discarded. When a single RNA aligned in multiple places, the alignment having the highest base identity was identified. Only alignments having a base identity level within 0.5% of the best and at least 25% ba
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