The Role of Bioinformatics in Personalized Medicine: Your Future Medical Treatment
DOI:
https://doi.org/10.55175/cdk.v46i12.399Kata Kunci:
: Bioinformatics, CADD, personalized medicine, randomized algorithmAbstrak
Bioinformatics is beneficial in personalized medicine. Two methods stand out, the randomized algorithm and computer assisted drug design (CADD). This article will discuss application, pitfalls, and future of those two methods. Suggestion to improve the clarity of the bioinformatics research in the field of personalized medicine will also be reviewed.
Bioinformatika berperan sangat penting dalam personalized medicine. Dua metode penting dalam kajian ini adalah randomized algorithm dan computer assisted drug design (CADD). Kajian ini membahas aplikasi, kekurangan, dan masa depan kedua metode tersebut. Saran-saran untuk meningkatkan efek riset bioinformatika dalam kajian personalized medicine juga akan ditelaah.
Unduhan
Referensi
Hesper B, Hogeweg P. Bioinformatica: Een werkconcept. Kameleon. 1970;1(6):28–9.
Hogeweg P. The roots of bioinformatics in theoretical biology. PLoS Comput Biol [Internet]. 2011 Mar [cited 2019 Jun 13];7(3):e1002021. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21483479
Ouzounis CA. Rise and demise of bioinformatics? Promise and progress. PLoS Comput Biol [Internet]. 2012. Available from: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002487
Nation U. World population prospects - Population division - United Nations [Internet]. 2019 [cited 2019 Jul 19]. Available from: https://population.un.org/wpp/
Badan Pusat Statistik. Sensus penduduk tahun 2010 [Internet]. 2010. Available from: http://sp2010.bps.go.id/index.php/site/index
Huang T, Shu Y, Cai YD. Genetic differences among ethnic groups. BMC Genomics [Internet]. 2015 Dec 21 [cited 2019 Jun 13];16:1093. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26690364
Vogenberg FR, Isaacson BC, Pursel M. Personalized medicine: Part 1: Evolution and development into theranostics. P T [Internet]. 2010 Oct [cited 2019 Jun 13];35(10):560–76. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21037908
Verma M. Personalized medicine and cancer. J Pers Med [Internet]. 2012 Jan 30 [cited 2019 Jun 13];2(1):1–14. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25562699
Gyeman AA, Ofori-Asenso R. Perspective: Does personalized medicine hold the future for medicine? J Pharm Bioallied Sci [Internet]. 2015 [cited 2019 Jun 13];7(3):239–44. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26229361
Pasipoularides A. Genomic translational research: Paving the way to individualized cardiac functional analyses and personalized cardiology. Int J Cardiol [Internet]. 2017 Mar 1 [cited 2019 Jun 13];230:384–401. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28057368
Pareek CS, Smoczynski R, Tretyn A. Sequencing technologies and genome sequencing. J Appl Genet [Internet]. 2011 Nov [cited 2019 Jun 13];52(4):413–35. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21698376
Zhang J, Chiodini R, Badr A, Zhang G. The impact of next-generation sequencing on genomics. J Genet Genomics [Internet]. 2011 Mar 20 [cited 2019 Jun 13];38(3):95–109. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21477781
Parikesit AA. Kontribusi aplikasi medis dari ilmu bioinformatika berdasarkan perkembangan pembelajaran mesin (machine learning) terbaru. Cermin Dunia Kedokt [Internet]. 2018;45(9):700–3. Available from: http://www.kalbemed.com/DesktopModules/EasyDNNNews/DocumentDownload.ashx?portalid=0&moduleid=471&articleid=225&documentid=65
Yu MJ. Natural product-like virtual libraries: Recursive atom-based enumeration. J Chem Inf Model [Internet]. 2011 Mar 28 [cited 2014 Aug 8];51(3):541–57. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21388152
Becker AS, Marcon M, Ghafoor S, Wurnig MC, Frauenfelder T, Boss A. Deep learning in mammography diagnostic accuracy of a multipurpose image analysis software in the detection of breast cancer. Invest Radiol. 2017;52(7):434-40.
Ramanto KN, Parikesit AA. The usage of deep learning algorithm in medical diagnostic of breast cancer. Malaysian J Fundam Appl Sci [Internet]. 2019 Apr 18 [cited 2019 Apr 18];15(2):274–81. Available from: https://mjfas.utm.my/index.php/mjfas/article/view/1231
Aworunse OS, Adeniji O, Oyesola OL, Isewon I, Oyelade J, Obembe OO. Genomic interventions in medicine. Bioinform Biol Insights [Internet]. 2018 [cited 2019 Jun 13];12:1177932218816100. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30546257
Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol [Internet]. 2017 Dec [cited 2019 Jun 13];2(4):230–43. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29507784
Sharma A. Randomized algorithms - GeeksforGeeks [Internet]. 2019 [cited 2019 Jun 13]. Available from: https://www.geeksforgeeks.org/randomized-algorithms/
Patel J, Sanjay S, Salanke G. A survey on randomized algorithms and its applications. Int J Adv Trends Comput Appl [Internet]. 2017;4(3):1–6. Available from: https://www.academia.edu/34988262/A_Survey_on_Randomized_Algorithms_and_its_Applications
Anaraki FP. Randomized algorithms for large-scale data analysis. Electr Comput Energy Eng Grad Theses Diss [Internet]. 2017 Apr 1 [cited 2019 Jun 13]. Available from: https://scholar.colorado.edu/ecen_gradetds/141
Liu W, Ye M, Wei J, Hu X. Fast constrained spectral clustering and cluster ensemble with random projection. Comput Intell Neurosci [Internet]. 2017 Sep 25 [cited 2019 Jun 13];2017:1–14. Available from: https://www.hindawi.com/journals/cin/2017/2658707/
Ming X, Feng Y, Liu R, Yang C, Zhou L, Zhai H, et al. A measurement-based generalized source model for Monte Carlo dose simulations of CT scans. Phys Med Biol. 2017;62(5):1759-76.
Çatli S. High-density dental implants and radiotherapy planning: Evaluation of effects on dose distribution using pencil beam convolution algorithm and Monte Carlo method. J Appl Clin Med Phys. 2015;16(5):46–52.
Fröhlich H, Balling R, Beerenwinkel N, Kohlbacher O, Kumar S, Lengauer T, et al. From hype to reality: data science enabling personalized medicine. BMC Med [Internet]. 2018 [cited 2019 Jun 13];16(1):150. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30145981
Chou KC. Structural bioinformatics and its impact to biomedical science. Curr Med Chem [Internet]. 2004 Aug [cited 2012 Nov 20];11(16):2105–34. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15279552
Muegge I. Selection criteria for drug-like compounds. Vol. 23, Medicinal Research Reviews. 2003. p. 302–21.
Leelananda SP, Lindert S. Computational methods in drug discovery. Beilstein J Org Chem [Internet]. 2016 [cited 2019 Jun 13];12:2694–718. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28144341
Drugbank. Saquinavir [Internet]. 2019. Available from: https://www.drugbank.ca/drugs/DB01232
Drugbank. Amprenavir [Internet]. 2019. Available from: https://www.drugbank.ca/drugs/DB00701
Drugbank. Dorzolamide [Internet]. 2019. Available from: https://www.drugbank.ca/drugs/DB00869
Scholler P, Zwier JM, Trinquet E, Rondard P, Pin JP, Prézeau L, et al. Time-resolved förster resonance energy transfer-based technologies to investigate G proteincoupled receptor machinery: High-throughput screening assays and future development. Prog Mol Biol Transl Sci. 2013;113:275-312.
Koehn FE, Carter GT. The evolving role of natural products in drug discovery. Nat Rev Drug Discov [Internet]. 2005 Mar [cited 2014 Jul 11];4(3):206–20. Available from: http://dx.doi.org/10.1038/nrd1657
Xia X. Position weight matrix, Gibbs sampler, and the associated significance tests in motif characterization and prediction. Scientifica (Cairo) [Internet]. 2012 [cited 2019 Jun 13];2012:1–15. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24278755
Xia X. Bioinformatics and drug discovery. Curr Top Med Chem. 2017;17(15):1709–26.
Dibyajyoti S, Talha Bin E, Swati P. Bioinformatics: The effects on the cost of drug discovery. Gall Med J [Internet]. 2013 May 8 [cited 2019 Jul 19];18(1):44. Available from: https://gmj.sljol.info/article/10.4038/gmj.v18i1.5511/
Wang C, Xu P, Zhang L, Huang J, Zhu K, Luo C. Current strategies and applications for precision drug design. Front Pharmacol [Internet]. 2018 [cited 2019 Jun 13];9:787. Available from: http://www.ncbi.nlm.nih.gov/pubmed/30072901
Akbar Z, Handoko LT. GRID architecture through a public cluster. In: Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global links for human development. IEEE [Internet]. 2008 [cited 2016 Aug 12]:1016–8. Available from: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4580761
Witarto AB. Bioinformatika: Mengawinkan teknologi informasi dengan bioteknologi trendnya di dunia dan prospeknya di Indonesia [Internet]. 2003. Available from: http://www.komputasi.lipi.go.id/data/1014224403/data/1110939469.pdf
Yanuar A, Mun’im A, Lagho ABA, Syahdi RR, Rahmat M, Suhartanto H. Medicinal plants database and three dimensional structure of the chemical compounds from medicinal plants in Indonesia. Int J Comput Sci [Internet]. 2011 Nov 28 [cited 2014 Mar 23];8(5):180–3. Available from: http://arxiv.org/abs/1111.7183
Afendi FM, Okada T, Yamazaki M, Hirai-Morita A, Nakamura Y, Nakamura K, et al. KNApSAcK family databases: Integrated metabolite-plant species databases for multifaceted plant research. Plant Cell Physiol. 2012;53(2)
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2019 https://creativecommons.org/licenses/by-nc/4.0/
Artikel ini berlisensi Creative Commons Attribution-NonCommercial 4.0 International License.
