Kontribusi Aplikasi Medis dari Ilmu Bioinformatika Berdasarkan Perkembangan Pembelajaran Mesin (Machine Learning) Terbaru
DOI:
https://doi.org/10.55175/cdk.v50i9.729Kata Kunci:
Bioinformatika, biomedis, biologi molekuler, biologi sistem, kecerdasan buatan, pembelajaran mesinAbstrak
Berkembangnya ilmu bioinformatika merupakan konsekuensi banyaknya data eksperimen laboratorium para peneliti biologi molekuler ataupun biomedis. Selain pengembangan basis data terpusat yang merupakan kompetensi inti ilmu bioinformatika, pendekatan komputasi lain seperti pembelajaran mesin juga dikembangkan, sehingga data tersebut dapat diolah menjadi informasi yang berguna bagi dunia kesehatan. Kajian ini akan menelaah perkembangan pendekatan pembelajaran mesin pada ilmu bioinformatika, dan aplikasinya pada dunia kesehatan terutama pada informatika kanker dan virus. Masa depan aplikasi medis dengan ilmu bioinformatika menarik karena melibatkan berbagai pendekatan baru seperti kecerdasan buatan dan biologi sistem.
The development of bioinformatics science is a consequence of the massive data generation of laboratory experiments conducted by molecular biology and biomedical researchers. In addition to the development of a centralized database that is the core competence of bioinformatics science, other computing approaches such as machine learning are also developed so that the data can be processed into useful information for the human health. This review will examine the development of machine learning approaches in bioinformatics science, and its application to the human health, especially in cancer and virus informatics. The future of medical applications with bioinformatics science is exciting as it involves various new approaches such as artificial intelligence and system biology.
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Brusic V. The growth of bioinformatics. Briefings in bioinformatics [Internet]. 2007 Dec 19 [cited 2016 Sep 6];8(2):69–70. Available from: http://bib.oxfordjournals.org/cgi/doi/10.1093/bib/bbm008
Hagen JB. The origins of bioinformatics. Nat Rev Genet [Internet]. 2000 Dec [cited 2015 Jan 28];1(3):231–6. Available from: http://dx.doi.org/10.1038/35042090
Claverie JM, Notredame C. Bioinformatics for dummies [Internet]. 2011. Available from: http://books.google.co.id/books?id=4Tw0aZBnBLEC
Tambunan USF, Parikesit AA. Cracking the genetic code of human virus by using open source bioinformatics tools. Malaysian J Fundam Appl Sci [Internet]. 2010;6(1):42–50. Available from: http://mjfas.ibnusina.utm.my/index.php/jfs/article/view/41
Welch L, Lewitter F, Schwartz R, Brooksbank C, Radivojac P, Gaeta B, et al. Bioinformatics curriculum guidelines: Toward a definition of core competencies. PLoS Comput Biol [Internet]. 2014 Mar 6 [cited 2016 Nov 28];10(3):e1003496. Available from: http://dx.plos.org/10.1371/journal.pcbi.1003496
Serapião CNF, AB de S. Bioinformatics: Strategies, trends, and perspectives. In: Lazinica A, editor. New advanced technologies [Internet]. 2010 [cited 2014 Aug 13]:126-14-. Available from: http://www.intechopen.com/books/new-advanced-technologies/bioinformatics-strategies-trends-and-perspectives
Collins FS, McKusick VA. Implications of the human genome project for medical science. JAMA [Internet]. 2001 Feb 7 [cited 2013 Aug 16];285(5):540–4. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11176855
Parikesit AA, Anugoro D, Putranto RA. Pemanfaatan bioinformatika dalam bidang pertanian dan kesehatan (The utilization of bioinformatics in the field of agriculture and health). E-Journal Menara Perkeb [Internet]. 2017 Oct 30 [cited 2017 Oct 31];85(2). Available from: http://mp.iribb.org/index.php/mpjurnal/article/view/237
Lunshof JE, Bobe J, Aach J, Angrist M, Thakuria JV, Vorhaus DB, et al. Personal genomes in progress: From the human genome project to the personal genome project. Dialogues Clin Neurosci [Internet]. 2010 Jan [cited 2013 Aug 16];12(1):47–60. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3181947&tool=pmcentrez&rendertype=abstract
NCBI. The NCBI handbook [Internet]. 2013 [cited 2013 Aug 1]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK21101/
Kumar D, Sarvate A, Singh S, Priya P. Virtual screening using machine learning approach. In: 2013 IEEE conference on information and communication technologies [Internet]. 2013 [cited 2014 Mar 10]:594–9. Available from: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6558164
Juhl Jensen L, Bateman A. The rise and fall of supervised machine learning techniques. Bioinformatics [Internet]. 2011;27:3331–2. Available from: http://bioinformatics.oxfordjournals.org/cgi/doi/10.1093/bioinformatics/btr585
Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, et al. DrugBank: A knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 2008;36(Database issue):901–6.
Moise L, De Groot AS. Putting immunoinformatics to the test. Nat Biotechnol [Internet]. 2006 Jul [cited 2015 Jan 28];24(7):791–2. Available from: http://dx.doi.org/10.1038/nbt0706-791
WHO. World Health Organization HIV/AIDS resource center [Internet]. 2018 [cited 2018 Apr 26]. Available from: http://www.who.int/hiv/en/
Kuroda DG, Bauman JD, Challa JR, Patel D, Troxler T, Das K, et al. Snapshot of the equilibrium dynamics of a drug bound to HIV-1 reverse transcriptase. Nat Chem [Internet]. 2013 Mar [cited 2018 Apr 11];5(3):174–81. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23422558
Tambunan USF, Alkaff AH, Nasution MAF. Bioinformatics approach to screening and developing drug against Ebola. In: Advances in Ebola control [Internet]. 2018 [cited 2018 May 2]:75–88. Available from: https://www.intechopen.com/books/advances-in-ebola-control/bioinformatics-approach-to-screening-anddeveloping-drug-against-ebola
De Lima Morais DA, Fang H, Rackham OJL, Wilson D, Pethica R, Chothia C, et al. SUPERFAMILY 1.75 including a domain-centric gene ontology method. Nucleic Acids Res [Internet]. 2011 Jan 9 [cited 2014 Jul 10];39(Database issue):427-34. Available from: http://nar.oxfordjournals.org/content/early/2010/11/08/nar.gkq1130.short
Tambunan USF, Bakri R, Parikesit AA, Ariyani T, Puspitasari RD, Kerami D. In silico modification of Zn 2+ binding group of suberoylanilide hydroxamic acid (SAHA) by organoselenium compounds as Homo sapiens class II HDAC inhibitor of cervical cancer. IOP Conf Ser Mater Sci Eng [Internet]. 2016 Feb 5 [cited 2016 Mar 17];107(1):012054. Available from: http://iopscience.iop.org/article/10.1088/1757-899X/107/1/012054
Michels KB, zur Hausen H. HPV vaccine for all. Lancet [Internet]. 2009 Jul 25 [cited 2013 Nov 20];374(9686):268–70. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19586657
American Cancer Society. Cancer facts & figures 2013. Vol. 2010, American Cancer Society. 2013.
Tundidor Y, García-Hernández CP, Pupo A, Infante YC, Rojas G. Delineating the functional map of the interaction between nimotuzumab and the epidermal growth factor receptor. MAbs [Internet]. 2014 Jul 23 [cited 2018 May 4];6(4):1013–25. Available from: http://www.tandfonline.com/doi/abs/10.4161/mabs.28915
Whittaker PA. What is the relevance of bioinformatics to pharmacology? Vol. 24, Trends in Pharmacological Sciences; 2003. p. 434–9.
Desany B, Zhang Z. Bioinformatics and cancer target discovery. Vol. 9, Drug Discovery Today; 2004. p. 795–802.
Lin JH, Lu AY. Role of pharmacokinetics and metabolism in drug discovery and development. Pharmacol Rev [Internet]. 1997 Dec [cited 2013 Apr 15];49(4):403–49. Available from: http://www.ncbi.nlm.nih.gov/pubmed/9443165
Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: New perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res [Internet]. 2017 Jan 4 [cited 2018 May 4];45(D1):D353–61. Available from: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw1092
Cherkasov A, Hilpert K, Jenssen H, Fjell CD, Waldbrook M, Mullaly SC, et al. Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs. ACS Chem Biol [Internet]. 2009 Jan 16 [cited 2018 May 4];4(1):65–74. Available from: http://pubs.acs.org/doi/abs/10.1021/cb800240j
Suhartanto H, Yanuar A, Wibisono A. Performance analysis cluster and GPU computing environment on molecular dynamic simulation of BRV-1 and REM2 with GROMACS. 2012 Oct 16 [cited 2013 Aug 16]; Available from: http://arxiv.org/abs/1210.4251
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