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转录因子数据库大全-biostar经典帖子系列

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发表于 2016-9-6 16:07:05 | 显示全部楼层 |阅读模式
摘抄自biostar网站,先放在这里,根据后缀名 -biostar经典帖子系列 可以提取所有帖子,将来做统一整理!
https://www.biostars.org/p/150185/
https://www.biostars.org/p/15798/


Here is some of the databases:

1) JasPar

2) MotifMap

3) TRANSFAC Matrix models

4) UniPROBE

5) Human Protein-DNA Interactome (hPDI)

6) Factorbook

7) DBD - TF prediction db

8) HOCOMOCO



In addition there is CIS-BP which includes the motifs from almost all of those database and more! You can then use all the motifs you're interested in and a program like FIMO to find all the motif occurrences and make a bed file

Here is another list of DBs:

http://meme-suite.org/db/motifs

here are the number of TBFs that have matrix models associated with it.

TRANSFAC Matrix models
One important point to know is that not all the matrix models are experimentally curated or good. So not all models can be used from TRANSFAC.
JASPAR is another one mentioned above with high quality matrix models.
UniPROBE
Human Protein-DNA Interactome (hPDI)
Factorbook
Or else there are other services which use JASPAR data: e.g. MAPPER database (http://genome.ufl.edu/mapper/) and oPOSSUM (http://www.cisreg.ca/oPOSSUM2_dev/help.html).
The sites you can see are from ENCODE. There are experimentally confirmed sites from ChIP-seq experiments. They were identified in a particular cell type from a single individual. They will differ between cell types and may also differ between individuals.

Not sure about all the databases you mention, but I know about Jaspar. Jaspar has motifs, not binding sites. These are short sequences of DNA that are known to attract transcription factor binding. You can use the motifs to predict where in the genome transcription factors might bind, however there is not necessarily experimental evidence that the transcription factor ever does.

Because of the random cutting step in ChIP-seq (fragments around 200bp), binding sites will be much larger than motifs (even though the region occupied by the transcription factor may not be much bigger than the motif).

Enrichr

http://amp.pharm.mssm.edu/Enrichr/



上一篇:SIB生信中心的ExPASy关于bioinformatics的分类是最优吗?
下一篇:现在开始学习生物信息会太晚了吗?
你这个问题很复杂,需要打赏,请点击 http://www.bio-info-trainee.com/donate 进行打赏,谢谢
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发表于 2016-12-5 19:59:28 | 显示全部楼层
感谢你提供这么好的帖子!
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发表于 2017-2-4 18:49:10 | 显示全部楼层

1
JasPar
http://jaspardev.genereg.net/



2
MotifMap
http://motifmap.ics.uci.edu/



3
TRANSFAC Matrix models
http://www.gene-regulation.com/pub/databases.html



4
UniPROBE
http://the_brain.bwh.harvard.edu/uniprobe/browse.php



5
Human Protein-DNA Interactome(hPDI)
http://bioinfo.wilmer.jhu.edu/PDI/FAQ.html



6
Factorbook
http://v1.factorbook.org/mediawi ... lcome_to_factorbook



7
DBD - TF prediction db
http://www.transcriptionfactor.org/index.cgi?Home



8
HOCOMOCO
http://hocomoco.autosome.ru/



最后分享一个转录因子相关数据库列表:
http://meme-suite.org/db/motifs


这个网页列出了1429个数据库,分别有真核生物、原核生物、人的、小鼠的……各种转录因子数据库,点击可以查看介绍。(小编建议收藏网址~)
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发表于 2017-5-30 22:21:47 | 显示全部楼层
楼主,您好!请问用R 有没有什么包可以实现:筛选出转录组表达芯片差异基因后,将差异表达基因聚类到该物种已知的转录因子(不是转录因子的下游靶基因,而是与转录因子可能有结合的蛋白,比如a基因对应的蛋白与转录因子b结合成蛋白复合体,继而形式功能,就是将差异基因聚类到与不用转录因子结合的蛋白“组”中),然后根据p值和聚类的个数排序。
这个功能是否需要自己建数据库?还是有现成的数据库呢?我看论坛上你提供的几个数据库都是预测转录因子可能的作用基因。
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