Literature DB >> 35713871

Integration of Transcriptomics Data and Metabolomic Data Using Biomedical Literature Mining and Pathway Analysis.

Archana Prabahar1.   

Abstract

Recent progress in omics technologies such as transcriptomics and metabolomics offers an unprecedented opportunity to understand the disease mechanisms and determines the associated biomedical entities using biomedical literature mining. Tremendous data available in the biomedical literature helps in addressing complex biomedical problems. Advancements in genomics and transcriptomics helps in decoding the genetic information obtained from various high throughput techniques for its use in personalized medicine and therapeutics. Integration of data from biomedical literature and data from large-scale genomic studies aids in the determination of the etiology of a disease and drug targets. This chapter addresses the perspectives of transcriptomics and metabolomics in biomedical literature mining and gives an overview of state-of-the-art techniques in this field.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Big data mining; Literature mining; Metabolomics; Personalized medicine; Transcriptomics

Mesh:

Year:  2022        PMID: 35713871     DOI: 10.1007/978-1-0716-2305-3_16

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  62 in total

1.  PubMed: http://www.pubmed.org.

Authors:  M R Macleod
Journal:  J Neurol Neurosurg Psychiatry       Date:  2002-12       Impact factor: 10.154

Review 2.  Metabolic profiles of cancer cells.

Authors:  Julian L Griffin; John P Shockcor
Journal:  Nat Rev Cancer       Date:  2004-07       Impact factor: 60.716

3.  Better prediction by use of co-data: adaptive group-regularized ridge regression.

Authors:  Mark A van de Wiel; Tonje G Lien; Wina Verlaat; Wessel N van Wieringen; Saskia M Wilting
Journal:  Stat Med       Date:  2015-09-13       Impact factor: 2.373

4.  Improved breast cancer prognosis through the combination of clinical and genetic markers.

Authors:  Yijun Sun; Steve Goodison; Jian Li; Li Liu; William Farmerie
Journal:  Bioinformatics       Date:  2006-11-26       Impact factor: 6.937

5.  DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays.

Authors:  Amrit Singh; Casey P Shannon; Benoît Gautier; Florian Rohart; Michaël Vacher; Scott J Tebbutt; Kim-Anh Lê Cao
Journal:  Bioinformatics       Date:  2019-09-01       Impact factor: 6.937

6.  Similarity network fusion for aggregating data types on a genomic scale.

Authors:  Bo Wang; Aziz M Mezlini; Feyyaz Demir; Marc Fiume; Zhuowen Tu; Michael Brudno; Benjamin Haibe-Kains; Anna Goldenberg
Journal:  Nat Methods       Date:  2014-01-26       Impact factor: 28.547

7.  HMDB 3.0--The Human Metabolome Database in 2013.

Authors:  David S Wishart; Timothy Jewison; An Chi Guo; Michael Wilson; Craig Knox; Yifeng Liu; Yannick Djoumbou; Rupasri Mandal; Farid Aziat; Edison Dong; Souhaila Bouatra; Igor Sinelnikov; David Arndt; Jianguo Xia; Philip Liu; Faizath Yallou; Trent Bjorndahl; Rolando Perez-Pineiro; Roman Eisner; Felicity Allen; Vanessa Neveu; Russ Greiner; Augustin Scalbert
Journal:  Nucleic Acids Res       Date:  2012-11-17       Impact factor: 16.971

8.  KEGG Atlas mapping for global analysis of metabolic pathways.

Authors:  Shujiro Okuda; Takuji Yamada; Masami Hamajima; Masumi Itoh; Toshiaki Katayama; Peer Bork; Susumu Goto; Minoru Kanehisa
Journal:  Nucleic Acids Res       Date:  2008-05-13       Impact factor: 16.971

9.  ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network.

Authors:  Dokyoon Kim; Ruowang Li; Scott M Dudek; Marylyn D Ritchie
Journal:  BioData Min       Date:  2013-12-20       Impact factor: 2.522

10.  SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer.

Authors:  Zhi Huang; Xiaohui Zhan; Shunian Xiang; Travis S Johnson; Bryan Helm; Christina Y Yu; Jie Zhang; Paul Salama; Maher Rizkalla; Zhi Han; Kun Huang
Journal:  Front Genet       Date:  2019-03-08       Impact factor: 4.599

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