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Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.

Bayrak, T ; Çetin, Z ; et al.
In: Medical & biological engineering & computing, Jg. 60 (2022-10-01), Heft 10, S. 2877-2897
Online academicJournal

Titel:
Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.
Autor/in / Beteiligte Person: Bayrak, T ; Çetin, Z ; Saygılı, Eİ ; Ogul, H
Link:
Zeitschrift: Medical & biological engineering & computing, Jg. 60 (2022-10-01), Heft 10, S. 2877-2897
Veröffentlichung: New York, NY : Springer ; <i>Original Publication</i>: Stevenage, Eng., Peregrinus., 2022
Medientyp: academicJournal
ISSN: 1741-0444 (electronic)
DOI: 10.1007/s11517-022-02641-w
Schlagwort:
  • Gene Ontology
  • Humans
  • Colorectal Neoplasms drug therapy
  • Colorectal Neoplasms genetics
  • Machine Learning
Sonstiges:
  • Nachgewiesen in: MEDLINE
  • Sprachen: English
  • Publication Type: Journal Article
  • Language: English
  • [Med Biol Eng Comput] 2022 Oct; Vol. 60 (10), pp. 2877-2897. <i>Date of Electronic Publication: </i>2022 Aug 10.
  • MeSH Terms: Colorectal Neoplasms* / drug therapy ; Colorectal Neoplasms* / genetics ; Machine Learning* ; Gene Ontology ; Humans
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  • Contributed Indexing: Keywords: Classification; Colorectal cancer; Druggable gene; Gene expression; Machine-learning; Tumor location
  • Entry Date(s): Date Created: 20220810 Date Completed: 20220913 Latest Revision: 20220913
  • Update Code: 20231215

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