Bibliographies thématiques / BIOINFORMATICIANS

Littérature scientifique sur le sujet « BIOINFORMATICIANS »

Auteur : Grafiati
Publié le 11 septembre 2023

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Articles de revues sur le sujet "BIOINFORMATICIANS"

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Chang, Jeffrey. « Core services : Reward bioinformaticians ». Nature 520, no 7546 (avril 2015) : 151–52. http://dx.doi.org/10.1038/520151a.

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Smaglik, Paul. « Who makes the best bioinformaticians ? » Nature 409, no 6822 (février 2001) : 963. http://dx.doi.org/10.1038/35057448.

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Niiler, Eric. « Bioinformaticians develop new data mining tools ». Nature Medicine 6, no 10 (octobre 2000) : 1071. http://dx.doi.org/10.1038/80375.

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Gómez-López, Gonzalo, Joaquín Dopazo, Juan C. Cigudosa, Alfonso Valencia et Fátima Al-Shahrour. « Precision medicine needs pioneering clinical bioinformaticians ». Briefings in Bioinformatics 20, no 3 (25 octobre 2017) : 752–66. http://dx.doi.org/10.1093/bib/bbx144.

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Pérez-Wohlfeil, Esteban, Oscar Torreno, Louisa J. Bellis, Pedro L. Fernandes, Brane Leskosek et Oswaldo Trelles. « Training bioinformaticians in High Performance Computing ». Heliyon 4, no 12 (décembre 2018) : e01057. http://dx.doi.org/10.1016/j.heliyon.2018.e01057.

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Zhang, Jianzhi. « EVOLUTION FOR BIOINFORMATICIANS AND BIOINFORMATICS FOR EVOLUTIONISTS ». Evolution 59, no 10 (octobre 2005) : 2281–83. http://dx.doi.org/10.1111/j.0014-3820.2005.tb00937.x.

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Zhang, Jianzhi. « EVOLUTION FOR BIOINFORMATICIANS AND BIOINFORMATICS FOR EVOLUTIONISTS1 ». Evolution 59, no 10 (2005) : 2281. http://dx.doi.org/10.1554/br05-9.1.

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Xue, Yu, et Xiu-Jie Wang. « Bioinformaticians wrestling with the big biomedical data ». Journal of Genetics and Genomics 44, no 5 (mai 2017) : 223–25. http://dx.doi.org/10.1016/j.jgg.2017.05.002.

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Müller, H. M., H. Fiegl, M. Widschwendter et G. Goebel. « Gene Methylation Data – a New Challenge for Bioinformaticians ? » Methods of Information in Medicine 44, no 04 (2005) : 516–19. http://dx.doi.org/10.1055/s-0038-1634002.

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Summary Objectives: Changes in the status of DNA methylation, known as epigenetic alterations, are among the most common molecular alterations in human neoplasia. For the first time, we reported on the analysis of fecal DNA from patients with CRC to determine the feasibility, sensitivity and specificity of this approach. We want to present basic information about DNA methylation analysis in the context of bioinformatics, the study design and several statistical experiences with gene methylation data. Additionally we outline chances and new research questions in the field of DNA methylation. Methods: We present current approaches to DNA methylation analysis based on one reference study. Its study design and the statistical analysis is reflected in the context of biomarker development. Finally we outline perspectives and research questions for statisticians and bioinformaticians. Results: Identification of at least three genes as potential DNA methylation-based tumor marker genes (SFRP2, SFRP5, PGR). Conclusions: DNA methylation analysis is a rising topic in molecular genetics. Gene methylation will push the extension of biobanks to include new types of genetic data. Study design and statistical methods for the detection of methylation biomarkers must be improved. For the purpose of establishing methylation analysis as a new diagnostic/prognostic tool the adaptation of several approaches has become a challenging field of research activity.
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Oshlack, Alicia. « A 10-step guide to party conversation for bioinformaticians ». Genome Biology 14, no 1 (2013) : 104. http://dx.doi.org/10.1186/gb-2013-14-1-104.

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Thèses sur le sujet "BIOINFORMATICIANS"

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Anders, Patrizia. « A bioinformaticians view on the evolution of smell perception ». Thesis, University of Skövde, School of Humanities and Informatics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-30.

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Background:

The origin of vertebrate sensory systems still contains many mysteries and thus challenges to bioinformatics. Especially the evolution of the sense of smell maintains important puzzles, namely the question whether or not the vomeronasal system is older than the main olfactory system. Here I compare receptor sequences of the two distinct systems in a phylogenetic study, to determine their relationships among several different species of the vertebrates.

Results:

Receptors of the two olfactory systems share little sequence similarity and prove to be a challenge in multiple sequence alignment. However, recent dramatical improvements in the area of alignment tools allow for better results and high confidence. Different strategies and tools were employed and compared to derive a

high quality alignment that holds information about the evolutionary relationships between the different receptor types. The resulting Maximum-Likelihood tree supports the theory that the vomeronasal system is rather an ancestor of the main olfactory system instead of being an evolutionary novelty of tetrapods.

Conclusions:

The connections between the two systems of smell perception might be much more fundamental than the common architecture of receptors. A better understanding of these parallels is desirable, not only with respect to our view on evolution, but also in the context of the further exploration of the functionality and complexity of odor perception. Along the way, this work offers a practical protocol through the jungle of programs concerned with sequence data and phylogenetic reconstruction.

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Livres sur le sujet "BIOINFORMATICIANS"

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1965-, Wong Limsoon, dir. The practical bioinformatician. Singapore : World Scientific Pub. Co., 2004.

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Widłak, Wiesława. Molecular Biology - Not Only for Bioinformaticians. Springer, 2013.

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Molecular Biology Not Only For Bioinformaticians. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

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Widłak, Wiesława. Molecular Biology - Not Only for Bioinformaticians. Springer Berlin / Heidelberg, 2013.

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Wong, Limsoon. The Practical Bioinformatician. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/5547.

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Wong, Limsoon. The Practical Bioinformatician. World Scientific Publishing Company, 2004.

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The practical bioinformatician. Singapore : World Scientific Pub. Co., 2005.

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Pezzella, Francesco, Mahvash Tavassoli et David J. Kerr, dir. Oxford Textbook of Cancer Biology. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198779452.001.0001.

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The study of the biology of tumours has grown to become markedly interdisciplinary, involving chemists, statisticians, epidemiologists, mathematicians, bioinformaticians, and computer scientists alongside medical scientists. Oxford Textbook of Cancer Biology brings together the developments from different branches of research into one volume. Structured in seven sections, the book starts with a review of the development and biology of multicellular organisms, how they maintain a healthy homeostasis in an individual, and a description of the molecular basis of cancer development. The book then illustrates how, once cells become neoplastic, their signalling network is altered and pathological behaviour follows. Changes that cancer cells can induce in nearby normal tissue are explored, and the new relationship established between them and the stroma is explicated. Finally, the authors illustrate the contribution provided by high throughput techniques to map cancer at different levels, from genomic sequencing to cellular metabolic functions, and how information technology with its vast amounts of data are integrated with traditional cell biology to provide a global view of the disease. The book concludes by summarizing what we know to date about cancer, and in what direction our understanding of cancer is moving.
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Publishing, Big Biomedical. Don't Panic ! I'm a Professional Bioinformatician : Customized 100 Page Lined Notebook Journal Gift for a Bioinformatician : Much Better Than a Throw Away Greeting or Birthday Card. Independently Published, 2020.

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Publishing, Big Biology. Don't Panic ! I'm a Professional Principal Bioinformatician : Customized 100 Page Lined Notebook Journal Gift for a Principal Bioinformatician : Much Better Than a Throw Away Greeting or Birthday Card. Independently Published, 2020.

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Chapitres de livres sur le sujet "BIOINFORMATICIANS"

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Sheikh, Mona A., et Yaniv Erlich. « Base-Calling for Bioinformaticians ». Dans Bioinformatics for High Throughput Sequencing, 67–83. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_5.

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Mias, George. « A Wolfram Language Primer for Bioinformaticians ». Dans Mathematica for Bioinformatics, 7–65. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72377-8_2.

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Phillips, Mark. « Key Law and Policy Considerations for Clinical Bioinformaticians ». Dans Translational Bioinformatics, 337–57. Dordrecht : Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-017-7543-4_14.

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Guo, Yang, Richard Townsend et Lam C. Tsoi. « Simple Analysis of Deposited Gene Expression Datasets for the Non-Bioinformatician : How to Use GEO for Fibrosis Research ». Dans Fibrosis, 511–25. New York, NY : Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7113-8_31.

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Bruskiewich, R., et S. Wanchana. « C4 rice : brainstorming from bioinformaticians ». Dans Charting New Pathways to C4 Rice, 381–98. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812709523_0023.

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Guo, Yan, Shilin Zhao, Margot Bjoring et Leng Han. « Advanced Datamining Using RNAseq Data ». Dans Big Data Analytics in Bioinformatics and Healthcare, 1–20. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6611-5.ch001.

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In recent years, RNA sequencing (RNAseq) technology has experienced a rapid rise in popularity. Often seen as a competitor of and the ultimate successor to microarray technology given its more accurate and quantitative gene expression measurement, RNAseq also offers a wealth of additional information that is often overlooked, and given the massive accumulation of RNAseq data available in public data repositories over the past few years, these data are ripe for discovery. Abundant opportunities exist for researchers to conduct in-depth, non-traditional analyses that take advantage of these secondary uses and for bioinformaticians to develop tools to make these data more accessible. This is discussed in this chapter.
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Zandavar, Hamed, et Mojtaba Afshari Babazad. « Secondary Metabolites : Alkaloids and Flavonoids in Medicinal Plants ». Dans Herbs and Spices - New Advances. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.108030.

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Secondary metabolites (SMs) are natural compounds produced mainly by bacteria, fungi, and plants. They are low molecular weight compounds that have a wide range of chemical structures and biological functions. Secondary metabolites are so named because, unlike primary metabolites such as lipids, amino acids, carbohydrates, and nucleic acids, their synthesis is not required for the organism’s development and reproduction. Today, the production of secondary metabolites is an important area of research for organic chemists, molecular biologists, and bioinformaticians. In this research, two types of secondary metabolites produced by plants, such as alkaloids and flavonoids, were studied and information was collected on the types of compounds, structures, biological activities, and commercial applications of these two types of secondary metabolites.
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« bioinformatician, n. » Dans Oxford English Dictionary. 3e éd. Oxford University Press, 2023. http://dx.doi.org/10.1093/oed/6659335015.

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El Naqa, Issam. « The Role of Big Data in Radiation Oncology ». Dans Big Data, 1519–42. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9840-6.ch069.

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More than half of cancer patients receive ionizing radiation as part of their treatment and it is the main modality at advanced stages of disease. Treatment outcomes in radiotherapy are determined by complex interactions between cancer genetics, treatment regimens, and patient-related variables. A typical radiotherapy treatment scenario can generate a large pool of data, “Big data,” that is comprised of patient demographics, dosimetry, imaging features, and biological markers. Radiotherapy data constitutes a unique interface between physical and biological data interactions. In this chapter, the authors review recent advances and discuss current challenges to interrogate big data in radiotherapy using top-bottom and bottom-top approaches. They describe the specific nature of big data in radiotherapy and discuss issues related to bioinformatics tools for data aggregation, sharing, and confidentiality. The authors also highlight the potential opportunities in this field for big data research from bioinformaticians as well as clinical decision-makers' perspectives.
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El Naqa, Issam. « The Role of Big Data in Radiation Oncology ». Dans Big Data Analytics in Bioinformatics and Healthcare, 164–85. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6611-5.ch008.

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More than half of cancer patients receive ionizing radiation as part of their treatment and it is the main modality at advanced stages of disease. Treatment outcomes in radiotherapy are determined by complex interactions between cancer genetics, treatment regimens, and patient-related variables. A typical radiotherapy treatment scenario can generate a large pool of data, “Big data,” that is comprised of patient demographics, dosimetry, imaging features, and biological markers. Radiotherapy data constitutes a unique interface between physical and biological data interactions. In this chapter, the authors review recent advances and discuss current challenges to interrogate big data in radiotherapy using top-bottom and bottom-top approaches. They describe the specific nature of big data in radiotherapy and discuss issues related to bioinformatics tools for data aggregation, sharing, and confidentiality. The authors also highlight the potential opportunities in this field for big data research from bioinformaticians as well as clinical decision-makers' perspectives.
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Actes de conférences sur le sujet "BIOINFORMATICIANS"

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Greenwood, M., C. Wroe, R. Stevens, C. Goble et M. Addis. « Are bioinformaticians doing e-Business ? » Dans EuroWeb 2002 Conference. BCS Learning & Development, 2002. http://dx.doi.org/10.14236/ewic/ew2002.8.

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Wu, Huanmei, et Amritha Palani. « Bioinformatics curriculum development and skill sets for bioinformaticians ». Dans 2015 IEEE Frontiers in Education Conference (FIE). IEEE, 2015. http://dx.doi.org/10.1109/fie.2015.7344321.

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Mandrekar, Jay. « Getting a statistician job you want : necessary skills for statistics graduates ». Dans Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17501.

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Many smart statistics graduates compete for the same job, but why does only one of them get selected? What separates him or her from the rest? Technical skill or soft skill or both? What does an employer look for in the candidate? Statisticians work as collaborators in various industries and academic institutions. In today’s competitive world, focusing only on mastering new statistical techniques and software is not enough. A candidate needs to strengthen soft skills. These include networking, communication, collaborative attitude, showcasing teamwork, and leadership potential. These skills are not generally taught in graduate coursework and may take time to deve- lop, but pay dividends when they come together. Graduate students should find a mentor who can guide them in achieving and mastering soft skills. Mentoring is a form of shared leadership which benefits both mentor and mentee, and is facilitated by many statistical associations. This paper will share insights from the author’s experience as a lead statistician over 15 years, as well as from his responsibilities as the director of biostatistics core at a large academic healthcare institute with over 300 statisticians, data scientists, bioinformaticians, and programmers. Examples will include one on one interactions, as well as a group setting with high school and university students.
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Pompei, Francesca, Valentina Castello, Alexandra Chiaverini, Amparo de Benito Armas, Sasha Del Vecchio, Joaquín Espí, Annalisa Falconi et al. « BECOMING A FOOD MICROBIAL BIOINFORMATICIAN : THE EXPERIENCE OF THE LEGO PROJECT ». Dans 14th annual International Conference of Education, Research and Innovation. IATED, 2021. http://dx.doi.org/10.21125/iceri.2021.2047.

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