Literature DB >> 23280501

Challenges and opportunities for oncology biomarker discovery.

Avisek Deyati1, Erfan Younesi, Martin Hofmann-Apitius, Natalia Novac.   

Abstract

Recent success of companion diagnostics along with the increasing regulatory pressure for better identification of the target population has created an unprecedented incentive for drug discovery companies to invest in novel strategies for biomarker discovery. In parallel with the rapid advancement and clinical adoption of high-throughput technologies, a number of knowledge management and systems biology approaches have been developed to analyze an ever increasing collection of OMICs data. This review discusses current biomarker discovery technologies highlighting challenges and opportunities of knowledge capturing and presenting a perspective of the future integrative modeling approaches as an emerging trend in biomarker prediction.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23280501     DOI: 10.1016/j.drudis.2012.12.011

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  17 in total

1.  From Molecules to Patients: The Clinical Applications of Translational Bioinformatics.

Authors:  K Regan; P R O Payne
Journal:  Yearb Med Inform       Date:  2015-08-13

2.  Text-mining in cancer research may help identify effective treatments.

Authors:  Yi-Wen Hsiao; Tzu-Pin Lu
Journal:  Transl Lung Cancer Res       Date:  2019-12

Review 3.  Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology.

Authors:  Harald Hampel; Nicola Toschi; Claudio Babiloni; Filippo Baldacci; Keith L Black; Arun L W Bokde; René S Bun; Francesco Cacciola; Enrica Cavedo; Patrizia A Chiesa; Olivier Colliot; Cristina-Maria Coman; Bruno Dubois; Andrea Duggento; Stanley Durrleman; Maria-Teresa Ferretti; Nathalie George; Remy Genthon; Marie-Odile Habert; Karl Herholz; Yosef Koronyo; Maya Koronyo-Hamaoui; Foudil Lamari; Todd Langevin; Stéphane Lehéricy; Jean Lorenceau; Christian Neri; Robert Nisticò; Francis Nyasse-Messene; Craig Ritchie; Simone Rossi; Emiliano Santarnecchi; Olaf Sporns; Steven R Verdooner; Andrea Vergallo; Nicolas Villain; Erfan Younesi; Francesco Garaci; Simone Lista
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

4.  Supervised Methods for Biomarker Detection from Microarray Experiments.

Authors:  Angela Serra; Luca Cattelani; Michele Fratello; Vittorio Fortino; Pia Anneli Sofia Kinaret; Dario Greco
Journal:  Methods Mol Biol       Date:  2022

Review 5.  Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic.

Authors:  Harald Hampel; Sid E O'Bryant; José L Molinuevo; Henrik Zetterberg; Colin L Masters; Simone Lista; Steven J Kiddle; Richard Batrla; Kaj Blennow
Journal:  Nat Rev Neurol       Date:  2018-11       Impact factor: 42.937

6.  Modeling factors critical for implementation of precision medicine at health systems-level: an IRT approach.

Authors:  John Jo Mogaka; Moses J Chimbari
Journal:  Am J Transl Res       Date:  2021-11-15       Impact factor: 4.060

Review 7.  Application of metabolomics in drug resistant breast cancer research.

Authors:  Ayesha N Shajahan-Haq; Mehar S Cheema; Robert Clarke
Journal:  Metabolites       Date:  2015-02-16

8.  Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids.

Authors:  Rick Jordan; Shyam Visweswaran; Vanathi Gopalakrishnan
Journal:  J Clin Bioinforma       Date:  2014-10-23

9.  Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning.

Authors:  Sze Chung Yuen; Xiaonan Liang; Hongmei Zhu; Yongliang Jia; Siu-Wai Leung
Journal:  Alzheimers Res Ther       Date:  2021-07-09       Impact factor: 6.982

10.  From integrative disease modeling to predictive, preventive, personalized and participatory (P4) medicine.

Authors:  Erfan Younesi; Martin Hofmann-Apitius
Journal:  EPMA J       Date:  2013-11-06       Impact factor: 6.543

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