Biological pattern discovery with R: machine learning approaches
"This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worl...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
New Jersey
World Scientific
[2022]
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Schlagworte: | |
Online-Zugang: | TUM01 TUM03 UBR01 Volltext |
Zusammenfassung: | "This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms"-- |
Beschreibung: | Includes bibliographical references and index |
Beschreibung: | 1 Online-Ressource (xiv, 447 Seiten) Illustrationen, Diagramme |
ISBN: | 9789811240126 9811240124 |
DOI: | 10.1142/12366 |
Internformat
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500 | |a Includes bibliographical references and index | ||
520 | |a "This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms"-- | ||
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Datensatz im Suchindex
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adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
author | Yang, Zheng Rong |
author_facet | Yang, Zheng Rong |
author_role | aut |
author_sort | Yang, Zheng Rong |
author_variant | z r y zr zry |
building | Verbundindex |
bvnumber | BV047579068 |
classification_tum | BIO 107 DAT 307 |
collection | ZDB-124-WOP |
ctrlnum | (ZDB-124-WOP)00012366 (OCoLC)1286868762 (DE-599)BVBBV047579068 |
dewey-full | 570.1/13 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 570 - Biology |
dewey-raw | 570.1/13 |
dewey-search | 570.1/13 |
dewey-sort | 3570.1 213 |
dewey-tens | 570 - Biology |
discipline | Biologie Informatik |
discipline_str_mv | Biologie Informatik |
doi_str_mv | 10.1142/12366 |
format | Electronic eBook |
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id | DE-604.BV047579068 |
illustrated | Not Illustrated |
index_date | 2024-07-03T18:32:53Z |
indexdate | 2024-07-10T09:15:22Z |
institution | BVB |
isbn | 9789811240126 9811240124 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032964473 |
oclc_num | 1286868762 |
open_access_boolean | |
owner | DE-355 DE-BY-UBR DE-M49 DE-BY-TUM |
owner_facet | DE-355 DE-BY-UBR DE-M49 DE-BY-TUM |
physical | 1 Online-Ressource (xiv, 447 Seiten) Illustrationen, Diagramme |
psigel | ZDB-124-WOP ZDB-124-WOP TUM_Einzelkauf_2022 ZDB-124-WOP UBR Einzelkauf 2022 |
publishDate | 2022 |
publishDateSearch | 2022 |
publishDateSort | 2022 |
publisher | World Scientific |
record_format | marc |
spelling | Yang, Zheng Rong Verfasser aut Biological pattern discovery with R machine learning approaches Zheng Rong Yang New Jersey World Scientific [2022] 1 Online-Ressource (xiv, 447 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms"-- Biological systems Simulation methods Pattern recognition systems Electronic books Erscheint auch als Druck-Ausgabe 978-981-124-011-9 981-124-011-6 Erscheint auch als Online-Ausgabe 978-981-124-013-3 https://doi.org/10.1142/12366 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Yang, Zheng Rong Biological pattern discovery with R machine learning approaches Biological systems Simulation methods Pattern recognition systems |
title | Biological pattern discovery with R machine learning approaches |
title_auth | Biological pattern discovery with R machine learning approaches |
title_exact_search | Biological pattern discovery with R machine learning approaches |
title_exact_search_txtP | Biological pattern discovery with R machine learning approaches |
title_full | Biological pattern discovery with R machine learning approaches Zheng Rong Yang |
title_fullStr | Biological pattern discovery with R machine learning approaches Zheng Rong Yang |
title_full_unstemmed | Biological pattern discovery with R machine learning approaches Zheng Rong Yang |
title_short | Biological pattern discovery with R |
title_sort | biological pattern discovery with r machine learning approaches |
title_sub | machine learning approaches |
topic | Biological systems Simulation methods Pattern recognition systems |
topic_facet | Biological systems Simulation methods Pattern recognition systems |
url | https://doi.org/10.1142/12366 |
work_keys_str_mv | AT yangzhengrong biologicalpatterndiscoverywithrmachinelearningapproaches |