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Gotowe bibliografie tematyczne / Bioinformatics / Artykuły w czasopismach

Artykuły w czasopismach na temat „Bioinformatics”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 7 lipca 2024

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1

Bottomley, S. "Bioinformatics: guide for evaluating bioinformatic software". Drug Discovery Today 4, nr 5 (1.05.1999): 240–43. http://dx.doi.org/10.1016/s1359-6446(99)01352-5.

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Eldəniz qızı Əhmədova, Gülnarə. "Inclusion of bioinformatics in biological sciences". NATURE AND SCIENCE 22, nr 7 (17.07.2022): 82–86. http://dx.doi.org/10.36719/2707-1146/22/82-86.

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Bioinformatika hesablama və biologiya elmlərinin birləşməsi kimi müəyyən edilə bilər. Proteomika və genomika tədqiqatları nəticəsində yaranan məlumatların daşqını emal etmək və təhlil etmək üçün aktuallıq bioinformatikanın önəm və əhəmiyyət qazanmasına səbəb oldu. Bununla belə, onun multidissiplinar təbiəti həm biologiya, həm də hesablama sahəsində hazırlanmış mütəxəssisə unikal tələbat yaratmışdır. İcmalda bioinformatika sahəsini təşkil edən komponentlər və bioinformatika təhsili olan fərdlərin yetişdirilməsi üçün tələb olunan fərqli təhsil meyarları təsvir edilib. Məqalə həm də Malayziyada bioinformatikaya giriş və onun haqqında ümumi məlumat verəcəkdir. Malayziyada mövcud bioinformatika ssenarisi onun inkişafını ölçmək və gələcək bioinformatika təhsili strategiyalarını planlaşdırmaq üçün araşdırıldı. Müqayisə üçün biz digər ölkələrin təhsildə istifadə etdiyi metod və strategiyaları araşdırdıq ki, bioinformatikanın tətbiqini daha da təkmilləşdirmək üçün dərslər alınsın. Hesab olunur ki, akademiyadan, sənayedən dəqiq və kifayət qədər idarəetmə gələcəkdə keyfiyyətli bioinformatiklər yetişdirməyə imkan verəcək. Açar sözlər: bioinformatika, hesablama biologiyası, təhsil, biologiya elmi, bioinformatikanın tədrisi Gulnara Eldeniz Ahmadova Inclusion of bioinformatics in biological sciences Abstract Bioinformatics can be defined as the combination of computational and biological sciences. The urgency to process and analyze the flood of data resulting from proteomics and genomics research has led bioinformatics to gain prominence and importance. However, its multidisciplinary nature has created a unique need for a specialist trained in both biology and computing. In this review, we have described the components that make up the field of bioinformatics and the different educational criteria required to produce individuals with bioinformatics training. This article will also provide an introduction and overview of bioinformatics in Malaysia. The current bioinformatics scenario in Malaysia was examined to gauge its development and plan future bioinformatics education strategies. For comparison, we examined the methods and strategies used in education by other countries, so that lessons can be learned to further improve the application of bioinformatics. It is believed that accurate and sufficient management from academia and industry will enable to produce quality bioinformaticians in the future. Keywords: bioinformatics, computational biology, education, biological science, teaching bioinformatics

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3

Kangueane, Pandjassarame. "Biotechnology, Bioinformatics and BIOINFORMATION in an autobiography". Bioinformation 16, nr 1 (31.01.2020): 39–50. http://dx.doi.org/10.6026/97320630016039.

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4

Kangueane, Pandjassarame. "Biotechnology, Bioinformatics and BIOINFORMATION in an autobiography". Bioinformation 16, nr 1 (31.01.2020): 39–50. http://dx.doi.org/10.6026/97320630016050.

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5

Lee, Byung-Wook, In-Sun Chu, Nam-Shin Kim, Jin-Hyuk Lee, Seon-Yong Kim, Wan-Kyu Kim i Sang-Hyuk Lee. "Bioinformatics Resources of the Korean Bioinformation Center (KOBIC)". Genomics & Informatics 8, nr 4 (31.12.2010): 165–69. http://dx.doi.org/10.5808/gi.2010.8.4.165.

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6

Palsson, Bernhard O. "Bioinformatics: What lies beyond bioinformatics?" Nature Biotechnology 15, nr 1 (styczeń 1997): 3–4. http://dx.doi.org/10.1038/nbt0197-3.

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7

Santos, Sílvia Regina Cavani Jorge. "Bioinformatics". Brazilian Journal of Pharmaceutical Sciences 47, nr 1 (marzec 2011): 193. http://dx.doi.org/10.1590/s1984-82502011000100024.

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8

Brokaw, Stephen. "Bioinformatics:". Journal of Pharmaceutical Marketing & Management 16, nr 4 (13.10.2005): 65–80. http://dx.doi.org/10.1300/j058v16n04_04.

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9

Persidis, Aris. "Bioinformatics". Nature Biotechnology 17, nr 8 (sierpień 1999): 828–30. http://dx.doi.org/10.1038/11793.

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10

Doom, T., M. Raymerand i D. Krane. "Bioinformatics". IEEE Potentials 23, nr 1 (luty 2004): 24–27. http://dx.doi.org/10.1109/mp.2004.1266936.

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11

Scott, L. Ridgway. "Bioinformatics". Perspectives in Biology and Medicine 47, nr 1 (2004): 135–39. http://dx.doi.org/10.1353/pbm.2004.0015.

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12

Hofestädt, R. "Bioinformatics". Yearbook of Medical Informatics 11, nr 01 (sierpień 2002): 581–83. http://dx.doi.org/10.1055/s-0038-1638127.

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13

WATKINS, KAREN J. "BIOINFORMATICS". Chemical & Engineering News Archive 79, nr 8 (19.02.2001): 29–45. http://dx.doi.org/10.1021/cen-v079n008.p029.

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14

Bottomley, Steve. "Bioinformatics". Drug Discovery Today 3, nr 9 (wrzesień 1998): 426–28. http://dx.doi.org/10.1016/s1359-6446(98)01225-2.

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15

Bottomley, Steve, i Tim Littlejohn. "Bioinformatics". Drug Discovery Today 3, nr 11 (listopad 1998): 525–27. http://dx.doi.org/10.1016/s1359-6446(98)01255-0.

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16

Bottomley, Steve. "Bioinformatics". Drug Discovery Today 4, nr 1 (styczeń 1999): 42–44. http://dx.doi.org/10.1016/s1359-6446(98)01285-9.

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17

Bottomley, Steve. "Bioinformatics". Drug Discovery Today 4, nr 10 (październik 1999): 482–84. http://dx.doi.org/10.1016/s1359-6446(99)01398-7.

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18

Bottomley, Steve. "Bioinformatics". Drug Discovery Today 5, nr 6 (czerwiec 2000): 262–64. http://dx.doi.org/10.1016/s1359-6446(00)01504-x.

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19

Gattiker, James R., Jason T. L. Wang i Paul P. Wang. "Bioinformatics". Information Sciences 139, nr 1-2 (listopad 2001): 1–2. http://dx.doi.org/10.1016/s0020-0255(01)00154-2.

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20

Barber, Stuart. "Bioinformatics". Journal of Applied Statistics 36, nr 2 (16.12.2008): 235–36. http://dx.doi.org/10.1080/02664760802340275.

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21

Kaminski, Naftali. "Bioinformatics". American Journal of Respiratory Cell and Molecular Biology 23, nr 6 (grudzień 2000): 705–11. http://dx.doi.org/10.1165/ajrcmb.23.6.4291.

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22

Boguski, Mark S. "Bioinformatics". Current Opinion in Genetics & Development 4, nr 3 (czerwiec 1994): 383–88. http://dx.doi.org/10.1016/0959-437x(94)90025-6.

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23

Moore, Jason H. "Bioinformatics". Journal of Cellular Physiology 213, nr 2 (2007): 365–69. http://dx.doi.org/10.1002/jcp.21218.

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24

Benoît, Gerald. "Bioinformatics". Annual Review of Information Science and Technology 39, nr 1 (18.10.2006): 179–218. http://dx.doi.org/10.1002/aris.1440390112.

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25

Forman, Michele R., Sarah M. Greene, Nancy E. Avis, Stephen H. Taplin, Paul Courtney, Peter A. Schad, Bradford W. Hesse i Deborah M. Winn. "Bioinformatics". American Journal of Preventive Medicine 38, nr 6 (czerwiec 2010): 646–51. http://dx.doi.org/10.1016/j.amepre.2010.03.002.

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26

Pagel, Mark. "Evolution, Bioinformatics and Evolutionary Bioinformatics Online". Evolutionary Bioinformatics 2 (styczeń 2006): 117693430600200. http://dx.doi.org/10.1177/117693430600200006.

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27

Mshvidobadze, Tinatin. "Bioinformatics as Emerging Tool and Pipeline Frameworks". Science Progress and Research 1, nr 4 (23.10.2021): 411–15. http://dx.doi.org/10.52152/spr/2021.162.

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In this article, we will discuss the areas of origin of bioinformatics in the human health care system. Due to the growing network of biological information databases such as human genomes, transcriptomics and proteomics, bioinformatics has become the approach of choosing forensic sciences. High-throughput bioinformatic analyses increasingly rely on pipeline frameworks to process sequence and metadata. Here we survey and compare the design philosophies of several current pipeline frameworks.

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28

Brown Epstein, Helen-Ann. "Successful Support of Bioinformatics and Translational Bioinformatics". Journal of Hospital Librarianship 12, nr 3 (lipiec 2012): 266–71. http://dx.doi.org/10.1080/15323269.2012.692272.

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29

SoRelle, Jeffrey A., Megan Wachsmann i Brandi L. Cantarel. "Assembling and Validating Bioinformatic Pipelines for Next-Generation Sequencing Clinical Assays". Archives of Pathology & Laboratory Medicine 144, nr 9 (11.02.2020): 1118–30. http://dx.doi.org/10.5858/arpa.2019-0476-ra.

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Context.— Clinical next-generation sequencing (NGS) is being rapidly adopted, but analysis and interpretation of large data sets prompt new challenges for a clinical laboratory setting. Clinical NGS results rely heavily on the bioinformatics pipeline for identifying genetic variation in complex samples. The choice of bioinformatics algorithms, genome assembly, and genetic annotation databases are important for determining genetic alterations associated with disease. The analysis methods are often tuned to the assay to maximize accuracy. Once a pipeline has been developed, it must be validated to determine accuracy and reproducibility for samples similar to real-world cases. In silico proficiency testing or institutional data exchange will ensure consistency among clinical laboratories. Objective.— To provide molecular pathologists a step-by-step guide to bioinformatics analysis and validation design in order to navigate the regulatory and validation standards of implementing a bioinformatic pipeline as a part of a new clinical NGS assay. Data Sources.— This guide uses published studies on genomic analysis, bioinformatics methods, and methods comparison studies to inform the reader on what resources, including open source software tools and databases, are available for genetic variant detection and interpretation. Conclusions.— This review covers 4 key concepts: (1) bioinformatic analysis design for detecting genetic variation, (2) the resources for assessing genetic effects, (3) analysis validation assessment experiments and data sets, including a diverse set of samples to mimic real-world challenges that assess accuracy and reproducibility, and (4) if concordance between clinical laboratories will be improved by proficiency testing designed to test bioinformatic pipelines.

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30

Moreews, François, Olivier Sallou, Hervé Ménager, Yvan Le bras, Cyril Monjeaud, Christophe Blanchet i Olivier Collin. "BioShaDock: a community driven bioinformatics shared Docker-based tools registry". F1000Research 4 (14.12.2015): 1443. http://dx.doi.org/10.12688/f1000research.7536.1.

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Linux container technologies, as represented by Docker, provide an alternative to complex and time-consuming installation processes needed for scientiﬁc software. The ease of deployment and the process isolation they enable, as well as the reproducibility they permit across environments and versions, are among the qualities that make them interesting candidates for the construction of bioinformatic infrastructures, at any scale from single workstations to high throughput computing architectures. The Docker Hub is a public registry which can be used to distribute bioinformatic software as Docker images. However, its lack of curation and its genericity make it difﬁcult for a bioinformatics user to ﬁnd the most appropriate images needed. BioShaDock is a bioinformatics-focused Docker registry, which provides a local and fully controlled environment to build and publish bioinformatic software as portable Docker images. It provides a number of improvements over the base Docker registry on authentication and permissions management, that enable its integration in existing bioinformatic infrastructures such as computing platforms. The metadata associated with the registered images are domain-centric, including for instance concepts deﬁned in the EDAM ontology, a shared and structured vocabulary of commonly used terms in bioinformatics. The registry also includes user deﬁned tags to facilitate its discovery, as well as a link to the tool description in the ELIXIR registry if it already exists. If it does not, the BioShaDock registry will synchronize with the registry to create a new description in the Elixir registry, based on the BioShaDock entry metadata. This link will help users get more information on the tool such as its EDAM operations, input and output types. This allows integration with the ELIXIR Tools and Data Services Registry, thus providing the appropriate visibility of such images to the bioinformatics community.

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31

Abed, Raghad, i Yusra Al-Najjar. "Bioinformatics Storing Databases". Technium BioChemMed 2, nr 4 (12.12.2021): 96–105. http://dx.doi.org/10.47577/biochemmed.v2i4.5335.

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An exceptional branch of data that requires huge databases has been shown lately from genome sequencing projects which is a field that employs computational approaches to answer biological questions. With this huge sequence of information that is available for researchers, bioinformatics plays a big role in studying basic medical-biological problems. The challenge that faces bioinformatical scientists is to help in discovering genes and designing molecular models, site-directed mutagenesis, and other experiments that reveal the unknown relationships concerning the structure and function of genes and proteins. This become a big challenge especially with the huge amount of data that is generated using the human genome and other systematic sequencing efforts up till now. Bioinformatics solves biological problems depending on available data. It is concerned with creating databases and predicting the outcome of lab experiments.

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32

Brazas, M. D., J. T. Yamada i B. F. F. Ouellette. "Evolution in bioinformatic resources: 2009 update on the Bioinformatics Links Directory". Nucleic Acids Research 37, Web Server (15.06.2009): W3—W5. http://dx.doi.org/10.1093/nar/gkp531.

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33

Fraser, Lewis, Shaolin Liang, Simon Shiu i Julian Tanner. "Aptamer Bioinformatics". International Journal of Molecular Sciences 18, nr 12 (24.11.2017): 2516. http://dx.doi.org/10.3390/ijms18122516.

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34

Jain, Eric. "Practical Bioinformatics". Pharmacogenomics 4, nr 2 (marzec 2003): 119–21. http://dx.doi.org/10.1517/phgs.4.2.119.22634.

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Peach, H. F., P. W. M. Johnson, S. Johnson, L. K. Jones, M. Jones, R. Sharpe, E. Shaw i in. "Computational / bioinformatics". Annals of Oncology 23, suppl 5 (1.06.2012): v38—v40. http://dx.doi.org/10.1093/annonc/mds164.

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Jacobson, A. "Bioinformatics booming". Computing in Science & Engineering 4, nr 4 (lipiec 2002): 11. http://dx.doi.org/10.1109/mcise.2002.1014974.

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Tennant, Michele R. "Bioinformatics librarian". Reference Services Review 33, nr 1 (marzec 2005): 12–19. http://dx.doi.org/10.1108/00907320410519333.

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Alfred, Jane. "Bioinformatics lessons". Nature Reviews Genetics 2, nr 10 (październik 2001): 736. http://dx.doi.org/10.1038/35093531.

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39

Valverde, Jose R. "Bioinformatics Algorithms". EMBnet.journal 20 (16.07.2014): 781. http://dx.doi.org/10.14806/ej.20.0.781.

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Stafford, Ned. "Bioinformatics awarded". Genome Biology 5 (2004): spotlight—20040629–01. http://dx.doi.org/10.1186/gb-spotlight-20040629-01.

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Greaves, Sarah. "Virtual bioinformatics". Nature Reviews Genetics 5, nr 4 (kwiecień 2004): 246. http://dx.doi.org/10.1038/nrg1329.

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Youngs, Robin, i Edward Fisher. "Introducing bioinformatics". Journal of Laryngology & Otology 128, nr 10 (październik 2014): 847. http://dx.doi.org/10.1017/s0022215114002618.

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Voolstra, C. "Microarray Bioinformatics". Briefings in Functional Genomics and Proteomics 3, nr 3 (1.01.2004): 289–90. http://dx.doi.org/10.1093/bfgp/3.3.289.

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Samudrala, R. "Structural Bioinformatics". Briefings in Bioinformatics 4, nr 3 (1.01.2003): 299–301. http://dx.doi.org/10.1093/bib/4.3.299.

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Mostafa, Javed. "Whither Bioinformatics?" Obstetrics & Gynecology 123, nr 6 (czerwiec 2014): 1151–52. http://dx.doi.org/10.1097/aog.0000000000000312.

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46

Salter, Hugh. "Teaching bioinformatics". Biochemical Education 26, nr 1 (styczeń 1998): 3–10. http://dx.doi.org/10.1016/s0307-4412(97)00163-5.

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47

de Bono, Stephanie. "Bioinformatics boost". Trends in Biochemical Sciences 26, nr 7 (lipiec 2001): 413. http://dx.doi.org/10.1016/s0968-0004(01)01914-4.

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Dooley, Erin E. "Bioinformatics Organization". Environmental Health Perspectives 111, nr 6 (1.05.2003): a337. http://dx.doi.org/10.1289/ehp.111-a337.

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Jamison, D. C. "Open Bioinformatics". Bioinformatics 19, nr 6 (12.04.2003): 679–80. http://dx.doi.org/10.1093/bioinformatics/btg214.

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Lomberk, Gwen. "Bioinformatics tools". Pancreatology 5, nr 4-5 (styczeń 2005): 314–15. http://dx.doi.org/10.1159/000086531.

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