Bioinformatics approaches for Biomedical Research

Autores/as

  • Kasandra Aguilar Cázarez Centro de Investigación de Estudios Avanzados, Ciudad de México, México
  • Ernesto Andrade Collantes Universidad Autónoma de Sinaloa, Facultad de Ciencias Químico Biológicas, Sinaloa, México
  • Marisol Verdugo Meza Universidad Autónoma de Sinaloa, Facultad de Ciencias Químico Biológicas, Sinaloa, México
  • Claudia María de-la-Rocha-Morales Universidad Autónoma de Sinaloa, Facultad de Ciencias Químico Biológicas, Sinaloa, México
  • Cruz Fernando López-Carrera Instituto Politécnico Nacional, Escuela Nacional de Ciencias Biológicas, Ciudad de México, México
  • Paúl Alexis López-Durán Universidad Anáhuac México, Campus Norte, Facultad de Ciencias de la Salud, Estado de México, México.

DOI:

https://doi.org/10.36105/psrua.2022v2n3.04

Palabras clave:

bioinformática, biomedicina, genómica comparativa, biomarcadores, diseño computarizado de fármacos, diseño de vacunas, medicina personalizada

Resumen

An enormous amount of data is generated and compiled in several databases every year. Along with this, comes a demand for the analysis and interpretation of the entirety of this biological information. Taking care of this task, bioinformatics promises breakthroughs in research and development in complex biomedical areas. In just a few years since its beginning, bioinformatics has led to great progress and demonstrated its potential. It has created an opportunity to solve arising medical and molecular issues faster and more efficiently, as compared to the traditional approach. The present review aims to present some of the main applications of bioinformatics in the field of biomedicine, such as comparative genomics, biomarker identification, computer-aided drug design, vaccine design, and personalized medicine. In addition, we also cover some of its steadily reduced limitations.

Descargas

Los datos de descargas todavía no están disponibles.

PLUMX metrics

Citas

Hao S, Lv J, Yang Q, Wang A, Li Z, Guo Y, et al. Identification of Key Genes and Circular RNAs in Human Gastric Cancer. Med Sci Monit. 2019 Apr 5;25:2488–504. https://doi.org/10.12659/MSM.915382

Liu W, Ouyang S, Zhou Z, Wang M, Wang T, Qi Y, et al. Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases. Mol Genet Genomic Med [Internet]. 2019 Feb [cited 2021 Oct 9];7(2). Available from: https://onlinelibrary.wiley.com/doi/10.1002/mgg3.528

Bayat A. Science, medicine, and the future: Bioinformatics. BMJ. 2002 Apr 27;324(7344):1018–22. https://doi.org/10.1136/bmj.324.7344.1018

Akalın PK. Introduction to bioinformatics. Mol Nutr Food Res. 2006 Jul;50(7):610–9. https://doi.org/10.1002/mnfr.200500273

Xu J, McPartlon M, Li J. Improved protein structure prediction by deep learning irrespective of co-evolution information. Nat Mach Intell. 2021 Jul;3(7):601–9. https://doi.org/10.1038/s42256-021-00348-5

Padilla‐Rojas C, Jimenez‐Vasquez V, Hurtado V, Mestanza O, Molina IS, Barcena L, et al. Genomic analysis reveals a rapid spread and predominance of lambda (C.37) SARS‐COV‐2 lineage in Peru despite circulation of variants of concern. J Med Virol. 2021 Dec;93(12):6845–9. https://doi.org/10.1002/jmv.27261

Branco I, Choupina A. Bioinformatics: new tools and applications in life science and personalized medicine. Appl Microbiol Biotechnol. 2021 Feb;105(3):937–51. https://doi.org/10.1007/s00253-020-11056-2

Li Y, Tenchov R, Smoot J, Liu C, Watkins S, Zhou Q. A Comprehensive Review of the Global Efforts on COVID-19 Vaccine Development. ACS Cent Sci. 2021 Apr 28;7(4):512–33. https://doi.org/10.1021/acscentsci.1c00120

NIH N. Comparative Genomics [Internet]. Genome.gov. 2007. Available from: https://www.genome.gov/11006946/comparative-genomics

de Crécy-Lagard V, Hanson AD. Comparative Genomics ☆. In: Reference Module in Biomedical Sciences [Internet]. Elsevier; 2018 [cited 2021 Oct 8]. p. B9780128012383660000. Available from: https://linkinghub.elsevier.com/retrieve/pii/B9780128012383660956

Wei L, Liu Y, Dubchak I, Shon J, Park J. Comparative genomics approaches to study organism similarities and differences. J Biomed Inform. 2002 Apr;35(2):142–50. https://doi.org/10.1016/S1532-0464(02)00506-3

Setubal JC, Almeida NF, Wattam AR. Comparative Genomics for Prokaryotes. In: Setubal JC, Stoye J, Stadler PF, editors. Comparative Genomics [Internet]. New York, NY: Springer New York; 2018 [cited 2021 Oct 9]. p. 55–78. (Methods in Molecular Biology; vol. 1704). Available from: http://link.springer.com/10.1007/978-1-4939-7463-4_3

Hunt SY, Barnaby NG, Budowle B, Morse S. Forensic Microbiology. In: Encyclopedia of Microbiology [Internet]. Elsevier; 2009 [cited 2021 Oct 13]. p. 22–34. Available from: https://linkinghub.elsevier.com/retrieve/pii/B9780123739445002911

Díaz-Camacho SP, Parra-Unda JR, Ríos-Sicairos J, Delgado-Vargas F. Molecular Identification of the Etiological Agent of Human Gnathostomiasis in an Endemic Area of Mexico. Jpn J Infect Dis. 2020;73(1):44–50. https://doi.org/10.7883/yoken.JJID.2019.180

Boni MF, Lemey P, Jiang X, Lam TT-Y, Perry BW, Castoe TA, et al. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat Microbiol. 2020 Nov;5(11):1408–17. https://doi.org/10.1038/s41564-020-0771-4

López-Durán PA, Fonseca-Coronado S, Lozano-Trenado LM, Araujo-Betanzos S, Rugerio-Trujillo DA, Vaughan G, et al. Nosocomial transmission of extensively drug resistant Acinetobacter baumannii strains in a tertiary level hospital. Ozer EA, editor. PLOS ONE. 2020 Apr 17;15(4):e0231829. https://doi.org/10.1371/journal.pone.0231829

Mizutani S, Yamada T, Yachida S. Significance of the gut microbiome in multistep colorectal carcinogenesis. Cancer Sci. 2020 Mar;111(3):766–73. https://doi.org/10.1111/cas.14298

De Angelis M, Ferrocino I, Calabrese FM, De Filippis F, Cavallo N, Siragusa S, et al. Diet influences the functions of the human intestinal microbiome. Sci Rep. 2020 Dec;10(1):4247. https://doi.org/10.1038/s41598-020-61192-y

Cao S, Zhang W, Ding W, Wang M, Fan S, Yang B, et al. Structure and function of the Arctic and Antarctic marine microbiota as revealed by metagenomics. Microbiome. 2020 Dec;8(1):47. https://doi.org/10.1186/s40168-020-00826-9

Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001 Mar;69(3):89–95. https://doi.org/10.1067/mcp.2001.113989

Capecchi R, Puxeddu I, Pratesi F, Migliorini P. New biomarkers in SLE: from bench to bedside. Rheumatology. 2020 Dec 5;59(Supplement_5):v12–8. https://doi.org/10.1093/rheumatology/keaa484

Azad RK, Shulaev V. Metabolomics technology and bioinformatics for precision medicine. Brief Bioinform. 2019 Nov 27;20(6):1957–71. https://doi.org/10.1093/bib/bbx170

Telenti A. Integrating metabolomics with genomics. Pharmacogenomics. 2018 Dec;19(18):1377–81. https://doi.org/10.2217/pgs-2018-0155

Tsimberidou AM, Fountzilas E, Nikanjam M, Kurzrock R. Review of precision cancer medicine: Evolution of the treatment paradigm. Cancer Treat Rev. 2020 Jun;86:102019. https://doi.org/10.1016/j.ctrv.2020.102019

Grau J, Ben-Gal I, Posch S, Grosse I. VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees. Nucleic Acids Res. 2006 Jul 1;34(Web Server):W529–33. https://doi.org/10.1093/nar/gkl212

Toro-Domínguez D, Martorell-Marugán J, López-Domínguez R, García-Moreno A, González-Rumayor V, Alarcón-Riquelme ME, et al. ImaGEO: integrative gene expression meta-analysis from GEO database. Kelso J, editor. Bioinformatics. 2019 Mar 1;35(5):880–2. https://doi.org/10.1093/bioinformatics/bty721

Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016 Jul;17(7):451–9. https://doi.org/10.1038/nrm.2016.25

Rinschen MM, Ivanisevic J, Giera M, Siuzdak G. Identification of bioactive metabolites using activity metabolomics. Nat Rev Mol Cell Biol. 2019 Jun;20(6):353–67. https://doi.org/10.1038/s41580-019-0108-4

Maharjan M, Tanvir RB, Chowdhury K, Duan W, Mondal AM. Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies. BMC Bioinformatics. 2020 Dec;21(S9):218. https://doi.org/10.1186/s12859-020-3524-8

Song X, Du R, Gui H, Zhou M, Zhong W, Mao C, et al. Identification of potential hub genes related to the progression and prognosis of hepatocellular carcinoma through integrated bioinformatics analysis. Oncol Rep [Internet]. 2019 Nov 6 [cited 2021 Oct 13]; Available from: http://www.spandidos-publications.com/10.3892/or.2019.7400

Wan Y, Zhang X, Leng H, Yin W, Zeng W, Zhang C. Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis. PeerJ. 2020 Jul 9;8:e9120. https://doi.org/10.7717/peerj.9120

Gururajan A, Clarke G, Dinan TG, Cryan JF. Molecular biomarkers of depression. Neurosci Biobehav Rev. 2016 May;64:101–33. https://doi.org/10.1016/j.neubiorev.2016.02.011

Li W, Luo C, Xie X, Xiao Y, Zhao F, Cai J, et al. Identification of key genes and pathways in syphilis combined with diabetes: a bioinformatics study. AMB Express. 2020 Dec;10(1):83. https://doi.org/10.1186/s13568-020-01009-3

Chen P, Chen Y, Wu W, Chen L, Yang X, Zhang S. Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis. Aging. 2019 Aug 26;11(16):6469–89. https://doi.org/10.18632/aging.102200

Liu Y, Gu H-Y, Zhu J, Niu Y-M, Zhang C, Guo G-L. Identification of Hub Genes and Key Pathways Associated With Bipolar Disorder Based on Weighted Gene Co-expression Network Analysis. Front Physiol. 2019 Aug 20;10:1081. https://doi.org/10.3389/fphys.2019.01081

Leelananda SP, Lindert S. Computational methods in drug discovery. Beilstein J Org Chem. 2016 Dec 12;12:2694–718. https://doi.org/10.3762/bjoc.12.267

Silverman RB, Holladay MW. The organic chemistry of drug design and drug action. Third edition. Amsterdam ; Boston: Elsevier/AP, Academic Press, is an imprint of Elsevier; 2014. 517 p. https://doi.org/10.1016/C2009-0-64537-2

Kapetanovic IM. Computer-aided drug discovery and development (CADDD): In silico-chemico-biological approach. Chem Biol Interact. 2008 Jan;171(2):165–76. https://doi.org/10.1016/j.cbi.2006.12.006

Grinter S, Zou X. Challenges, Applications, and Recent Advances of Protein-Ligand Docking in Structure-Based Drug Design. Molecules. 2014 Jul 11;19(7):10150–76. https://doi.org/10.3390/molecules190710150

Acharya C, Coop A, E. Polli J, D. MacKerell A. Recent Advances in Ligand-Based Drug Design: Relevance and Utility of the Conformationally Sampled Pharmacophore Approach. Curr Comput Aided-Drug Des. 2011 Mar 1;7(1):10–22. https://doi.org/10.2174/157340911793743547

Elfiky AA. SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: an in silico perspective. J Biomol Struct Dyn. 2020 May 6;1–9. https://doi.org/10.1080/07391102.2020.1761882

Arya H, Bhatt TK. Role of Bioinformatics in Subunit Vaccine Design. In: Molecular Docking for Computer-Aided Drug Design [Internet]. Elsevier; 2021 [cited 2021 Oct 9]. p. 425–39. https://doi.org/10.1016/B978-0-12-822312-3.00013-8

Del Tordello E, Rappuoli R, Delany I. Reverse Vaccinology. In: Human Vaccines [Internet]. Elsevier; 2017 [cited 2021 Oct 13]. p. 65–86. https://doi.org/10.1016/B978-0-12-802302-0.00002-9

Chukwudozie OS, Duru VC, Ndiribe CC, Aborode AT, Oyebanji VO, Emikpe BO. The Relevance of Bioinformatics Applications in the Discovery of Vaccine Candidates and Potential Drugs for COVID-19 Treatment. Bioinforma Biol Insights. 2021 Jan;15. https://doi.org/10.1177/11779322211002168

Adu-Bobie J. Two years into reverse vaccinology. Vaccine. 2003 Jan 30;21(7–8):605–10. https://doi.org/10.1016/S0264-410X(02)00566-2

Rappuoli R. Reverse vaccinology. Curr Opin Microbiol. 2000 Oct;3(5):445–50. 10.1016/s1369-5274(00)00119-3

Seib KL, Zhao X, Rappuoli R. Developing vaccines in the era of genomics: a decade of reverse vaccinology. Clin Microbiol Infect. 2012 Oct;18:109–16. https://doi.org/10.1111/j.1469-0691.2012.03939.x

Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics. 2007 Dec;8(1):4. https://doi.org/10.1186/1471-2105-8-4

Dormitzer PR, Ulmer JB, Rappuoli R. Structure-based antigen design: a strategy for next generation vaccines. Trends Biotechnol. 2008 Dec;26(12):659–67. https://doi.org/10.1016/j.tibtech.2008.08.002

María RR, Arturo CJ, Alicia JA, Paulina MG, Gerardo AO. The Impact of Bioinformatics on Vaccine Design and Development. In: Afrin F, Hemeg H, Ozbak H, editors. Vaccines [Internet]. InTech; 2017 [cited 2021 Oct 13]. https://doi.org/10.5772/INTECHOPEN.69273

Ishack S, Lipner SR. Bioinformatics and immunoinformatics to support COVID‐19 vaccine development. J Med Virol. 2021 Sep;93(9):5209–11. https://doi.org/10.1002/jmv.27017

Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A. A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. Cell Host Microbe. 2020 Apr;27(4):671-680.e2. https://doi.org/10.1016/j.chom.2020.03.002

Abdelmageed MI, Abdelmoneim AH, Mustafa MI, Elfadol NM, Murshed NS, Shantier SW, et al. Design of multi epitope-based peptide vaccine against E protein of human COVID-19: An immunoinformatics approach [Internet]. Bioinformatics; 2020 Feb [cited 2021 Oct 13]. https://doi.org/10.1155/2020/2683286

Naithani N, Sinha S, Misra P, Vasudevan B, Sahu R. Precision medicine: Concept and tools. Med J Armed Forces India. 2021 Jul;77(3):249–57. https://doi.org/10.1016/j.mjafi.2021.06.021

Carrasco-Ramiro F, Peiró-Pastor R, Aguado B. Human genomics projects and precision medicine. Gene Ther. 2017 Sep;24(9):551–61. https://doi.org/10.1038/gt.2017.77

Sunil Krishnan G, Joshi A, Kaushik V. Bioinformatics in Personalized Medicine. In: Singh V, Kumar A, editors. Advances in Bioinformatics [Internet]. Singapore: Springer Singapore; 2021 [cited 2021 Oct 13]. p. 303–15. https://doi.org/10.1007/978-981-33-6191-1_15

Liu L, Song B, Ma J, Song Y, Zhang S-Y, Tang Y, et al. Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics. Comput Struct Biotechnol J. 2020;18:1587–604. https://doi.org/10.1016/j.csbj.2020.06.010

Chen L, Lu D, Sun K, Xu Y, Hu P, Li X, et al. Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis. Gene. 2019 Apr;692:119–25. https://doi.org/10.1016/j.gene.2019.01.001

Bhuvaneshwar K, Belouali A, Singh V, Johnson RM, Song L, Alaoui A, et al. G-DOC Plus – an integrative bioinformatics platform for precision medicine. BMC Bioinformatics. 2016 Dec;17(1):193. https://doi.org/10.1186/s12859-016-1010-0

Jünemann S, Kleinbölting N, Jaenicke S, Henke C, Hassa J, Nelkner J, et al. Bioinformatics for NGS-based metagenomics and the application to biogas research. J Biotechnol. 2017 Nov;261:10–23. https://doi.org/10.1016/j.jbiotec.2017.08.012

Muthiah I, Rajendran K, Dhanaraj P, Vallinayagam S. In silico structure prediction, molecular docking and dynamic simulation studies on G Protein-Coupled Receptor 116: a novel insight into breast cancer therapy. J Biomol Struct Dyn. 2021 Sep 2;39(13):4807–15. https://doi.org/10.1080/07391102.2020.1783365

Purkayastha A, Ditty SE, Su J, McGraw J, Hadfield TL, Tibbetts C, et al. Genomic and Bioinformatics Analysis of HAdV-4, a Human Adenovirus Causing Acute Respiratory Disease: Implications for Gene Therapy and Vaccine Vector Development. J Virol. 2005 Feb 15;79(4):2559–72. https://doi.org/10.1128/JVI.79.4.2559-2572.2005

Watson M, Warr A. Errors in long-read assemblies can critically affect protein prediction. Nat Biotechnol. 2019 Feb;37(2):124–6. https://doi.org/10.1038/s41587-018-0004-z

Wang A, Au KF. Performance difference of graph-based and alignment-based hybrid error correction methods for error-prone long reads. Genome Biol. 2020 Dec;21(1):14. https://doi.org/10.1186/s13059-019-1885-y

McGuire AL, Oliver JM, Slashinski MJ, Graves JL, Wang T, Kelly PA, et al. To share or not to share: A randomized trial of consent for data sharing in genome research: Genet Med. 2011 Nov;13(11):948–55. https://doi.org/10.1097/gim.0b013e3182227589

Oliver JM, Slashinski MJ, Wang T, Kelly PA, Hilsenbeck SG, McGuire AL. Balancing the Risks and Benefits of Genomic Data Sharing: Genome Research Participants’ Perspectives. Public Health Genomics. 2012;15(2):106–14. https://doi.org/10.1159/000334718

Bejleri J, Jirström E, Donovan P, Williams DJ, Pfeiffer S. Diagnostic and Prognostic Circulating MicroRNA in Acute Stroke: A Systematic and Bioinformatic Analysis of Current Evidence. J Stroke. 2021 May 31;23(2):162–82. https://doi.org/10.5853/jos.2020.05085

Ghadamyari F, Heidari MM, Zeinali S, Khatami M, Merat S, Bagherian H, et al. Mutational screening through comprehensive bioinformatics analysis to detect novel germline mutations in the APC gene in patients with familial adenomatous polyposis (FAP). J Clin Lab Anal [Internet]. 2021 May [cited 2021 Nov 17];35(5). Available from: https://doi.org/10.1002/jcla.23768

Sufyan M, Ali Ashfaq U, Ahmad S, Noor F, Hamzah Saleem M, Farhan Aslam M, et al. Identifying key genes and screening therapeutic agents associated with diabetes mellitus and HCV-related hepatocellular carcinoma by bioinformatics analysis. Saudi J Biol Sci. 2021 Oct;28(10):5518–25. https://doi.org/10.1016/j.sjbs.2021.07.068

Dopazo J, Maya-Miles D, García F, Lorusso N, Calleja MÁ, Pareja MJ, et al. Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System. J Pers Med. 2021 May 26;11(6):475.https://doi.org/10.3390/jpm11060475

Smith DR. The battle for user-friendly bioinformatics. Front Genet [Internet]. 2013 [cited 2021 Nov 17];4. Available from: https://doi.org/10.3389/fgene.2013.00187

PORTADA

Descargas

Publicado

2022-05-03

Cómo citar

Aguilar Cázarez, K. ., Andrade Collantes, E. ., Verdugo Meza, M. ., de-la-Rocha-Morales, C. M., López-Carrera C. F. ., & López-Durán P. A. . (2022). Bioinformatics approaches for Biomedical Research. Proceedings of Scientific Research Universidad Anáhuac. Multidisciplinary Journal of Healthcare, 2(3), 27–35. https://doi.org/10.36105/psrua.2022v2n3.04

Número

Sección

Review Articles

Compartir en: