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Journal articles on the topic 'Bioinformatics – Research'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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1

Lee, Eunjung, and Doheon Lee. "Systems Bioinformatics Research Trends." Journal of Korean Society of Medical Informatics 14, no. 4 (2008): 313. http://dx.doi.org/10.4258/jksmi.2008.14.4.313.

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2

Vandamme, Anne-Mieke. "Bioinformatics in virus research." Infection, Genetics and Evolution 7, no. 3 (2007): 353. http://dx.doi.org/10.1016/j.meegid.2007.04.001.

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3

Chen, Yi-Ping Phoebe, and Geoff McLachlan. "Bioinformatics Research in Australia." Asia-Pacific Biotech News 07, no. 03 (2003): 82–84. http://dx.doi.org/10.1142/s0219030303000211.

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Bioinformatics is the intersection of computer science, statistics, molecular biology and genetics. It is one of the most important emerging research areas of the 21st century and has already attracted worldwide interest. It is clear that major initiatives are being undertaken which will establish Australia both as a vital link in the international bioinformatics community for research and development and also as an Asia-Pacific service for bioinformatics. This article briefly notes some groups carrying out bioinformatics research in Australia.
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4

Lesko, L. J. "Drug Research and Translational Bioinformatics." Clinical Pharmacology & Therapeutics 91, no. 6 (2012): 960–62. http://dx.doi.org/10.1038/clpt.2012.45.

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5

Perez-Iratxeta, C., M. A. Andrade-Navarro, and J. D. Wren. "Evolving research trends in bioinformatics." Briefings in Bioinformatics 8, no. 2 (2006): 88–95. http://dx.doi.org/10.1093/bib/bbl035.

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6

Boulesteix, A. L. "Over-optimism in bioinformatics research." Bioinformatics 26, no. 3 (2009): 437–39. http://dx.doi.org/10.1093/bioinformatics/btp648.

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7

Ellis, Heidi J. C. "Undergraduate involvement in bioinformatics research." ACM SIGCSE Bulletin 38, no. 3 (2006): 322. http://dx.doi.org/10.1145/1140123.1140228.

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8

Iwakiri, Junichi, Michiaki Hamada, and Kiyoshi Asai. "Bioinformatics tools for lncRNA research." Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms 1859, no. 1 (2016): 23–30. http://dx.doi.org/10.1016/j.bbagrm.2015.07.014.

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9

Meier, René, Christoph Ruttkies, Hendrik Treutler, and Steffen Neumann. "Bioinformatics can boost metabolomics research." Journal of Biotechnology 261 (November 2017): 137–41. http://dx.doi.org/10.1016/j.jbiotec.2017.05.018.

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10

Lang, E. "Section 7: Bioinformatics: Bioinformatics and its Impact on Clinical Research Methods." Yearbook of Medical Informatics 15, no. 01 (2006): 104–6. http://dx.doi.org/10.1055/s-0038-1638478.

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SummaryTo summarize current excellent research in the field of bioinformatics.Synopsis of the articles selected for the IMIA Yearbook 2006. Results: Current research in the field of bioinformatics clearly shows ongoing unification of experimental findings and clinical outcomes. Microarray data, gene sequences and clinical data are more and more perceived as different but related facets of one entity. Significant work is done in the area of text and data mining in order to bring together patient data and biochemical phenomena by means of ontologies. A strong trend in the clinical field is performance of exhaustive studies on DNA material derived from patients that suffer from diseases that are already known to be inherited. Examination of appropriate methods covers data and text mining, ontologies as well as machine learning and classification.The best paper selection of articles on bioinformatics shows examples of excellent research on methods used for studying inherited diseases and their underlying genetic dispositions. Clinical studies, inclusion of experimental findings like microarray data, and of knowledge representation formats all lead to a better understanding the linkage between gene sequences, biological functions and clinical findings in the form of healthy state or physiological disorders.
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11

Luo, Jingchu. "Bioinformatics Service, Research and Education at CBI." Asia-Pacific Biotech News 07, no. 03 (2003): 93–95. http://dx.doi.org/10.1142/s0219030303000247.

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Bioinformatics plays an important role for in the research and development of the life science and biotechnology. This paper intends to give an overview of the activities of bioinformatics service, research and education at the Center of Bioinformatics, Peking University; the national node of the European Molecular Biology Network and the Asia Pacific Bioinformatics Network.
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12

Ong, Quang, Phuc Nguyen, Nguyen Phuong Thao, and Ly Le. "Bioinformatics Approach in Plant Genomic Research." Current Genomics 17, no. 4 (2016): 368–78. http://dx.doi.org/10.2174/1389202917666160331202956.

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13

Orlov, Yuriy L., Ralf Hofestädt, and Tatiana V. Tatarinova. "Bioinformatics research at BGRS\SB-2018." Journal of Bioinformatics and Computational Biology 17, no. 01 (2019): 1902001. http://dx.doi.org/10.1142/s0219720019020013.

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14

Kamble, Ashwini, and Rajesh Khairkar. "Basics of Bioinformatics in Biological Research." International Journal of Applied Sciences and Biotechnology 4, no. 4 (2017): 425–29. http://dx.doi.org/10.3126/ijasbt.v4i4.16252.

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The concept of laboratory rat is giving way to the computer mouse arose after the famous handshake between Clinton-Blair for the completion of the human genome in April 2003. Bioinformatics is defined as the application of computational techniques to understand and organize the information associated with biological macromolecules.There is availability of large databases of genomic information which has enabled research efforts for discovering methods for diagnosis and treatment of human diseases using DNA microarrays and proteomics experiments. But there are various problems while doing this like it’s always challenging to develop proper and sophisticated analysis method which can properly use genomic data bases considering its and heterogeneity of the data.The main purpose of this first paper is to explore and explain Bioinformatics in a more scientific way, and try highlighting applications of bioinformatics in the medical sector.Int J Appl Sci Biotechnol, Vol 4(4): 425-429
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15

Hwang, Ming-Jing, and Ching-Shu Suen. "Bioinformatics Research and Activities in Taiwan." Asia-Pacific Biotech News 10, no. 24 (2006): 1414–18. http://dx.doi.org/10.1142/s0219030306002126.

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16

Wong, Limsoon. "Bioinformatics Research and Activities in Singapore." Asia-Pacific Biotech News 10, no. 24 (2006): 1467–72. http://dx.doi.org/10.1142/s0219030306002205.

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17

Morishita, Shinichi. "A Unique Center for Bioinformatics Research." Asia-Pacific Biotech News 11, no. 15 (2007): 1068. http://dx.doi.org/10.1142/s0219030307001188.

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18

Lopes, Robson da Silva, Nathalia Maria Resende, Adenilda Cristina Honorio-França, and Eduardo Luzía França. "Application of Bioinformatics in Chronobiology Research." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/153839.

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Bioinformatics and other well-established sciences, such as molecular biology, genetics, and biochemistry, provide a scientific approach for the analysis of data generated through “omics” projects that may be used in studies of chronobiology. The results of studies that apply these techniques demonstrate how they significantly aided the understanding of chronobiology. However, bioinformatics tools alone cannot eliminate the need for an understanding of the field of research or the data to be considered, nor can such tools replace analysts and researchers. It is often necessary to conduct an evaluation of the results of a data mining effort to determine the degree of reliability. To this end, familiarity with the field of investigation is necessary. It is evident that the knowledge that has been accumulated through chronobiology and the use of tools derived from bioinformatics has contributed to the recognition and understanding of the patterns and biological rhythms found in living organisms. The current work aims to develop new and important applications in the near future through chronobiology research.
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19

Zhou, Ckeng, and Song-Nian Yu. "Using cluster computers in bioinformatics research." Journal of Shanghai University (English Edition) 7, no. 4 (2003): 370–74. http://dx.doi.org/10.1007/s11741-003-0012-0.

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20

Zhou, Jia, and Renee L. Sears. "Bioinformatics Approaches to Stem Cell Research." Current Pharmacology Reports 4, no. 4 (2018): 314–25. http://dx.doi.org/10.1007/s40495-018-0143-4.

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21

Whitfield, Eleanor J., Manuela Pruess, and Rolf Apweiler. "Bioinformatics database infrastructure for biotechnology research." Journal of Biotechnology 124, no. 4 (2006): 629–39. http://dx.doi.org/10.1016/j.jbiotec.2006.04.006.

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22

Gómez-López, Gonzalo, and Alfonso Valencia. "Bioinformatics and cancer research: building bridges for translational research." Clinical and Translational Oncology 10, no. 2 (2008): 85–95. http://dx.doi.org/10.1007/s12094-008-0161-5.

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23

Chang, I.-Shou, Ping-Chiang Lyu, Jenn-Kang Hwang, H. Sunny Sun, and Chao A. Hsiung. "Taiwan Bioinformatics Institute and the GMBD Bioinformatics Core." Asia-Pacific Biotech News 10, no. 24 (2006): 1432–34. http://dx.doi.org/10.1142/s0219030306002175.

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24

Wang, Xue Chen, Xiao Guang Yue, Qing Guo Ren, and Zi Qiang Zhao. "Research on Coal Mine Rescue Robot Model." Applied Mechanics and Materials 340 (July 2013): 801–4. http://dx.doi.org/10.4028/www.scientific.net/amm.340.801.

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According to the situation of frequently domestic mining safety accidents, the basic theory and related concepts of bioinformatics' gene expression programming and multi-agent system are discussed. Related concepts of Bioinformatics and biological evolution and evolutionary computation are described in this paper. A coal mine rescue robot working model is discussed based on bioinformatics gene expression programming algorithm and multi-agent system theory.
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25

Foote, S. J., T. Speed, and E. Handman. "What can Bioinformatics do for Parasitology Research?" Parasitology Today 14, no. 9 (1998): 346–47. http://dx.doi.org/10.1016/s0169-4758(98)01299-x.

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26

Sirintrapun, S. Joseph, Ahmet Zehir, Aijazuddin Syed, JianJiong Gao, Nikolaus Schultz, and Donavan T. Cheng. "Translational Bioinformatics and Clinical Research (Biomedical) Informatics." Surgical Pathology Clinics 8, no. 2 (2015): 269–88. http://dx.doi.org/10.1016/j.path.2015.02.015.

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27

Aoki-Kinoshita, Kiyoko F. "An Introduction to Bioinformatics for Glycomics Research." PLoS Computational Biology 4, no. 5 (2008): e1000075. http://dx.doi.org/10.1371/journal.pcbi.1000075.

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28

Romano, P., R. Giugno, and A. Pulvirenti. "Tools and collaborative environments for bioinformatics research." Briefings in Bioinformatics 12, no. 6 (2011): 549–61. http://dx.doi.org/10.1093/bib/bbr055.

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29

Ho, Jan-Ming, and Wen-Dar Lin. "Bioinformatics Research at CSCL, IIS, Academia Sinica." Asia-Pacific Biotech News 10, no. 24 (2006): 1427–29. http://dx.doi.org/10.1142/s0219030306002151.

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30

Bensmail, Halima, and Abdelali Haoudi. "Postgenomics: Proteomics and Bioinformatics in Cancer Research." Journal of Biomedicine and Biotechnology 2003, no. 4 (2003): 217–30. http://dx.doi.org/10.1155/s1110724303209207.

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Now that the human genome is completed, the characterization of the proteins encoded by the sequence remains a challenging task. The study of the complete protein complement of the genome, the “proteome,” referred to as proteomics, will be essential if new therapeutic drugs and new disease biomarkers for early diagnosis are to be developed. Research efforts are already underway to develop the technology necessary to compare the specific protein profiles of diseased versus nondiseased states. These technologies provide a wealth of information and rapidly generate large quantities of data. Processing the large amounts of data will lead to useful predictive mathematical descriptions of biological systems which will permit rapid identification of novel therapeutic targets and identification of metabolic disorders. Here, we present an overview of the current status and future research approaches in defining the cancer cell's proteome in combination with different bioinformatics and computational biology tools toward a better understanding of health and disease.
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31

Fuellen, Georg, James Adjaye, Aubrey de Grey, et al. "Bioinformatics in Aging Research: A Workshop Report." Rejuvenation Research 13, no. 6 (2010): 763–67. http://dx.doi.org/10.1089/rej.2010.1125.

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32

Raghothama, Chaerkady, H. C. Harsha, C. K. Prasad, and Akhilesh Pandey. "Bioinformatics and Proteomics Approaches for Aging Research." Biogerontology 6, no. 4 (2005): 227–32. http://dx.doi.org/10.1007/s10522-005-2617-0.

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33

Sirintrapun, S. Joseph, Ahmet Zehir, Aijazuddin Syed, JianJiong Gao, Nikolaus Schultz, and Donavan T. Cheng. "Translational Bioinformatics and Clinical Research (Biomedical) Informatics." Clinics in Laboratory Medicine 36, no. 1 (2016): 153–81. http://dx.doi.org/10.1016/j.cll.2015.09.013.

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34

Mulder, Nicola J., Ezekiel Adebiyi, Marion Adebiyi, et al. "Development of Bioinformatics Infrastructure for Genomics Research." Global Heart 12, no. 2 (2017): 91. http://dx.doi.org/10.1016/j.gheart.2017.01.005.

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35

Garg, Priyanka, and Pankaj Jaiswal. "Databases and bioinformatics tools for rice research." Current Plant Biology 7-8 (November 2016): 39–52. http://dx.doi.org/10.1016/j.cpb.2016.12.006.

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36

Ferguson, Adam R., Ellen D. Stück, and Jessica L. Nielson. "Syndromics: A Bioinformatics Approach for Neurotrauma Research." Translational Stroke Research 2, no. 4 (2011): 438–54. http://dx.doi.org/10.1007/s12975-011-0121-1.

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37

Cheng, Phil F. "Medical bioinformatics in melanoma." Current Opinion in Oncology 30, no. 2 (2018): 113–17. http://dx.doi.org/10.1097/cco.0000000000000428.

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38

Thornton, Janet, Graham Cameron, and Cath Brooksbank. "The European Bioinformatics Institute: Leading the bioinformatics revolution." Biochemist 26, no. 4 (2004): 33–38. http://dx.doi.org/10.1042/bio02604033.

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Life without databases is almost inconceivable to today's researchers in the biomolecular sciences -- the world of biomolecules is freely available on the Internet, along with a powerful set of tools for analysing the data. Many of the world's most widely used data resources are hosted and developed at the European Molecular Biology Laboratory (EMBL)'s European Bioinformatics Institute (EBI), often in collaboration with partners throughout the world. The EBI is also a thriving research centre.
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39

Jackman, Shaun D., Tatyana Mozgacheva, Susie Chen, et al. "ORCA: a comprehensive bioinformatics container environment for education and research." Bioinformatics 35, no. 21 (2019): 4448–50. http://dx.doi.org/10.1093/bioinformatics/btz278.

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Abstract Summary The ORCA bioinformatics environment is a Docker image that contains hundreds of bioinformatics tools and their dependencies. The ORCA image and accompanying server infrastructure provide a comprehensive bioinformatics environment for education and research. The ORCA environment on a server is implemented using Docker containers, but without requiring users to interact directly with Docker, suitable for novices who may not yet have familiarity with managing containers. ORCA has been used successfully to provide a private bioinformatics environment to external collaborators at a large genome institute, for teaching an undergraduate class on bioinformatics targeted at biologists, and to provide a ready-to-go bioinformatics suite for a hackathon. Using ORCA eliminates time that would be spent debugging software installation issues, so that time may be better spent on education and research. Availability and implementation The ORCA Docker image is available at https://hub.docker.com/r/bcgsc/orca/. The source code of ORCA is available at https://github.com/bcgsc/orca under the MIT license.
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40

Guo, Yu Qing, Fang Yu, and Ai Yuan Liu. "A Bibliometric Primary Study of Bioinformatics Research in China." Advanced Materials Research 282-283 (July 2011): 417–20. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.417.

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From 1997 to 2009, altogether 48059 pieces of literature on bioinformatics are extracted in SCI-Expended. Amongst them, 2853 pieces could be attributed to Chinese scholars. With NoteExpress, software that manages documents, the 48059 pieces of literature in the past 13 years were sorted using bibliometrical method. The main aim is to compare and assess the practices of bioinformatics research in China. This study examined the growth of the bioinformatics literature, in the world. The rank list was given according to different country. China’s total publication output comprises 2853 papers during the 13 years between 1997 and 2009 which was equivalent to 5.94% of the world output during the same period, and ranked the 4th. The year production and citations of papers on bioinformatics in 5 Asian countries and Taiwan district between 1997 and 2009 was compared. This study will provide general insights of bioinformatics research in China.
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41

Tabassum Khan, Nida. "The Emerging Role of Bioinformatics in Biotechnology." Journal of Biotechnology and Biomedical Science 1, no. 3 (2018): 13–24. http://dx.doi.org/10.14302/issn.2576-6694.jbbs-18-2173.

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Bioinformatic tools is widely used to manage the enormous genomic and proteomic data involving DNA/protein sequences management, drug designing, homology modelling, motif/domain prediction ,docking, annotation and dynamic simulation etc. Bioinformatics offers a wide range of applications in numerous disciplines such as genomics. Proteomics, comparative genomics, nutrigenomics, microbial genome, biodefense, forensics etc. Thus it offers promising future to accelerate scientific research in biotechnology
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42

Rana, KMS, K. Ahammad, and MA Salam. "Bioinformatics: scope and challenges in aquaculture research of Bangladesh- a review." International Journal of Agricultural Research, Innovation and Technology 10, no. 2 (2021): 137–45. http://dx.doi.org/10.3329/ijarit.v10i2.51587.

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Bioinformatics is one of the ongoing trends of biological research integrating gene based information and computational technology to produce new knowledge. It works to synthesize complex biological information from multiomics data (results of high throughput technologies) by employing a number of bioinformatics tools (software). User convenience and availability are the determining factors of these tools being widely used in bioinformatics research. BLAST, FASTA (FAST-All), EMBOSS, ClustalW, RasMol and Protein Explorer, Cn3D, Swiss PDB viewer, Hex, Vega, Bioeditor etc. are commonly operated bioinformatics software tools in fisheries and aquaculture research. By default, these software tools mine and analyze a vast biological data set using the available databases. However, aquaculture scientists can use bioinformatics for genomic data manipulation, genome annotation and expression profiling, molecular folding, modeling, and design as well as generating biological network and system biology. Therefore, they can contribute in specified fields of aquaculture such as disease diagnosis and aquatic health management, fish nutritional aspects and culture-able strain development. Although having huge prospects, Bangladesh is still in infancy of applying bioinformatics in aquaculture research with limited resources. Research council at national level should be formed to bring all the enthusiastic scientists and skilled manpower under a single umbrella and facilitate to contribute in a collaborative platform. Besides, fully-fledged bioinformatics degree should be launched at University levels to produce knowledgeable and trained work force for future research. This review was attempted to shed light on bioinformatics, as young integrated field of bio-computational research, and its significance in aquaculture research of Bangladesh.
 Int. J. Agril. Res. Innov. Tech. 10(2): 137-145, December 2020
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43

Sansom, Clare. "Bioinformatics in China." Biochemist 33, no. 5 (2011): 39–40. http://dx.doi.org/10.1042/bio03305039.

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The Cyberbiochemist theme for this special issue of The Biochemist devoted to China hardly needs stating: an overview, such as is possible in the space available, of bioinformatics – and genomics – research in the country that is the most populous on earth and that boasts the fastest growing economy of any major nation.
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44

Hicks, C. "Bioinformatics Project Streamlines Data Exchange." JNCI Journal of the National Cancer Institute 96, no. 8 (2004): 580. http://dx.doi.org/10.1093/jnci/96.8.580.

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45

Brenner, Chad. "Applications of Bioinformatics in Cancer." Cancers 11, no. 11 (2019): 1630. http://dx.doi.org/10.3390/cancers11111630.

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46

Zhang, Yun, Brian D. Aevermann, Tavis K. Anderson, et al. "Influenza Research Database: An integrated bioinformatics resource for influenza virus research." Nucleic Acids Research 45, no. D1 (2016): D466—D474. http://dx.doi.org/10.1093/nar/gkw857.

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47

Magana, Alejandra J., Manaz Taleyarkhan, Daniela Rivera Alvarado, Michael Kane, John Springer, and Kari Clase. "A Survey of Scholarly Literature Describing the Field of Bioinformatics Education and Bioinformatics Educational Research." CBE—Life Sciences Education 13, no. 4 (2014): 607–23. http://dx.doi.org/10.1187/cbe.13-10-0193.

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Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students’ attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education.
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48

Sensen, Christoph W. "Genome research and bioinformatics with relevance to biotechnology." Journal of Biotechnology 170 (January 2014): iv. http://dx.doi.org/10.1016/s0168-1656(13)00565-8.

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49

Grafström, Roland C., Rebecca Ceder, Bengt Fadeel, Karin Roberg, and Egon Willighagen. "Bioinformatics-based cancer research have wide toxicological applicability." Toxicology Letters 211 (June 2012): S160. http://dx.doi.org/10.1016/j.toxlet.2012.03.580.

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50

Ningrum, Dian Eka Aprilia Fitria, Imam Rofiki, Vannisa Aviana Melinda, Imroatul Hayyu Erfantinni, and Roiyan One Febriani. "Development of Biotechnology Textbook Based on Bioinformatics Research." Universal Journal of Educational Research 8, no. 11 (2020): 5188–96. http://dx.doi.org/10.13189/ujer.2020.081119.

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