GeneTopics--interpretation of gene sets via literature-driven topic models - Wikidata - wikimedia - TriplyDB

GeneTopics--interpretation of gene sets via literature-driven topic models

GeneTopics--interpretation of gene sets via literature-driven topic models

http://www.wikidata.org/entity/Q33642727

about

An overview of topic modeling and its current applications in bioinformatics Interdisciplinary dialogue for education, collaboration, and innovation: intelligent Biology and Medicine in and beyond 2013 Text mining for identifying topics in the literatures about adolescent substance use and depression

P2860

Q28078205-985F9709-97E9-4F81-B541-7A4FC6D7A200 Q33702055-97D8ABE2-9FBF-491D-8B17-6EDA1F98A28E Q35963529-B81864B6-7421-4F4B-9034-AF678ADB8341

P2860

GeneTopics--interpretation of gene sets via literature-driven topic models

http://www.wikidata.org/entity/Q33642727

description

2013 nî lūn-bûn

@nan

2013 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2013 թվականի դեկտեմբերին հրատարակված գիտական հոդված

@hy

2013年の論文

@ja

2013年論文

@yue

2013年論文

@zh-hant

2013年論文

@zh-hk

2013年論文

@zh-mo

2013年論文

@zh-tw

2013年论文

@wuu

name

GeneTopics--interpretation of gene sets via literature-driven topic models

@ast

GeneTopics--interpretation of gene sets via literature-driven topic models

@en

type

label

GeneTopics--interpretation of gene sets via literature-driven topic models

@ast

GeneTopics--interpretation of gene sets via literature-driven topic models

@en

prefLabel

GeneTopics--interpretation of gene sets via literature-driven topic models

@ast

GeneTopics--interpretation of gene sets via literature-driven topic models

@en

P1433

Q33642727-AE41E12C-9072-448B-B2C1-C3908D8445E2

P1476

Q33642727-05EBE49E-D059-4B3C-B3DD-B163848B7918

P2093

Q33642727-17F3DE37-393E-4FAA-A595-F4D3DEE9F2EF

Q33642727-3D594EEE-43B7-4207-8485-5BBD19C3623F

Q33642727-A0774CA9-A7DB-42C7-A1DB-6FFC4DA7F0C1

Q33642727-A27B64F4-DFB4-4355-8CDE-5878CC36E6E5

Q33642727-ADF4503A-52E7-438A-BAAD-680521E75834

P2860

Q33642727-1028F7B9-41E3-4A7F-98FB-A09267C0506B

Q33642727-18314404-4DE6-4326-BAA6-37E848FFC963

Q33642727-2F82CF50-6A04-4C82-B5C4-16D55A6D46B1

Q33642727-30F21D16-D3E7-4617-A37F-2F855322859F

Q33642727-4067723F-BDB0-406C-A7D7-94437E881D15

Q33642727-41BA0CCF-F7FF-4C1F-8A3C-5544EAA04F4B

Q33642727-89EB3C57-6F05-4C79-B38B-DE69B8DE11EB

Q33642727-9D16516C-D734-41B1-9EAA-768537176979

Q33642727-B30B11AC-3573-411D-A32A-87B833753039

Q33642727-B7B800D6-4ABD-4BA7-8E36-9A5A5B75FAF5

P2888

Q33642727-808C6BE4-0745-4452-8CEE-CCAB3947F2B8

P304

Q33642727-335D360F-C4A7-4699-A634-F7FFED21AE9C

P31

Q33642727-B74270A4-9BCA-4534-BBB1-350B2DF1CD9C

P356

Q33642727-9BA6BCFE-B5D1-4FB9-86ED-84DBB58B6D21

P478

Q33642727-CB6C0905-9E2D-46E4-B1E3-8E97C668B357

P577

Q33642727-A61C4281-AEE2-402B-8015-D7150BAE1E22

P5875

Q33642727-F610BAC1-B57F-4D89-BBCD-2941A9BB0A34

P6179

Q33642727-A9615E42-BB99-4E93-9272-5C83816858E2

P698

Q33642727-672C384B-A1A9-4A45-A7A2-3E7F000D5AEF

P921

Q33642727-1EE6C52F-DEF3-4909-B77C-2F7084392076

P932

Q33642727-B4AD2F5D-08DF-4316-93AA-EECAFAFB080B

P356

1752-0509-7-S5-S10

P1433

BMC Systems Biology

P1476

GeneTopics--interpretation of gene sets via literature-driven topic models

@en

P2093

Ahmed Enayetallah

http://www.w3.org/2001/XMLSchema#string

Daniel Ziemek

http://www.w3.org/2001/XMLSchema#string

Eric Fauman

http://www.w3.org/2001/XMLSchema#string

Li Xi

http://www.w3.org/2001/XMLSchema#string

Vicky Wang

http://www.w3.org/2001/XMLSchema#string

P2860

Transcriptional profile of isoproterenol-induced cardiomyopathy and comparison to exercise-induced cardiac hypertrophy and human cardiac failure

Gene ontology: tool for the unification of biology

KEGG: kyoto encyclopedia of genes and genomes

Human metabolic individuality in biomedical and pharmaceutical research

Finding complex biological relationships in recent PubMed articles using Bio-LDA

Reorganizing the protein space at the Universal Protein Resource (UniProt)

The genetic association database

2DDB - a bioinformatics solution for analysis of quantitative proteomics data.

Identifying biological concepts from a protein-related corpus with a probabilistic topic model.

A general modular framework for gene set enrichment analysis.

P2888

1752-0509-7-s5-s10

P304

S10

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1186/1752-0509-7-S5-S10

http://www.w3.org/2001/XMLSchema#string

P478

7 Suppl 5

http://www.w3.org/2001/XMLSchema#string

P577

2013-12-09T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

260377411

http://www.w3.org/2001/XMLSchema#string

P6179

1050956165

http://www.w3.org/2001/XMLSchema#string

P698

24564875

http://www.w3.org/2001/XMLSchema#string

P921

P932

4029197

http://www.w3.org/2001/XMLSchema#string