Artificial Intelligence in Bulk RNA-Seq: Challenges and Potential Solutions.
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| Title: | Artificial Intelligence in Bulk RNA-Seq: Challenges and Potential Solutions. |
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| Authors: | Rezapour M; Wake Forest Institute for Regenerative Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA., Trefry SV; Department of Biology, College of Science, George Mason University, Fairfax, VA 22030, USA.; School of Systems Biology, College of Science, George Mason University, Fairfax, VA 22030, USA., Opoku LA; School of Systems Biology, College of Science, George Mason University, Fairfax, VA 22030, USA., Narayanan A; Department of Biology, College of Science, George Mason University, Fairfax, VA 22030, USA. |
| Source: | Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2026 Apr 01; Vol. 35 (1), pp. 0039. Date of Electronic Publication: 2026 Apr 01 (Print Publication: 2026). |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology Country of Publication: Netherlands NLM ID: 101585369 Publication Model: eCollection Cited Medium: Print ISSN: 2001-0370 (Print) Linking ISSN: 20010370 NLM ISO Abbreviation: Comput Struct Biotechnol J Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2001-0370 |
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| DOI: | 10.34133/csbj.0039 |
