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9/21/2020 12:56:51 AM | Browse: 261 | Download: 552
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Received |
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2020-03-15 19:50 |
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Peer-Review Started |
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2020-03-17 00:24 |
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To Make the First Decision |
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Return for Revision |
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2020-04-18 21:12 |
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Revised |
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2020-06-06 16:00 |
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Second Decision |
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2020-07-01 10:33 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2020-07-01 22:42 |
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Articles in Press |
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2020-07-01 22:42 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2020-08-31 03:59 |
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Publish the Manuscript Online |
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2020-09-19 03:49 |
| ISSN |
2218-4333 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Genetics & Heredity |
| Manuscript Type |
Review |
| Article Title |
Powerful quantifiers for cancer transcriptomics
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Dumitru Andrei Iacobas |
| Funding Agency and Grant Number |
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| Corresponding Author |
Dumitru Andrei Iacobas, MSc, PhD, Director, Professor, Personalized Genomics Laboratory, CRI Center for Computational Systems Biology, Roy G Perry College of Engineering, Prairie View A&M University, Prairie View, TX 77446, United States. daiacobas@pvamu.edu |
| Key Words |
Cancer biomarkers; Cancer nodule; Gene therapy; Kidney cancer; Prostate cancer; RNA gene |
| Core Tip |
The Genomic Fabric Paradigm was developed as a holistic alternative to the biomarker approach of cancer transcriptomics. The genomic fabric of a functional pathway is the transcriptome associated with the most interconnected and stably expressed gene network responsible for that pathway. We present the associated analytical tools to characterize the topology, remodeling during cancer progression and in response to a therapy, and interplay of the genomic fabrics and identify the most legitimate targets in cancer gene therapy. The analyses are illustrated with examples from our transcriptomic studies on human cancer tissues and cell lines. |
| Publish Date |
2020-09-19 03:49 |
| Citation |
Iacobas DA. Powerful quantifiers for cancer transcriptomics. World J Clin Oncol 2020; 11(9): 679-704 |
| URL |
https://www.wjgnet.com/2218-4333/full/v11/i9/679.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v11.i9.679 |
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