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Titlebook: Machine Learning and Systems Biology in Genomics and Health; Shailza Singh Book 2022 The Editor(s) (if applicable) and The Author(s), unde

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樓主: Sediment
11#
發(fā)表于 2025-3-23 09:52:22 | 只看該作者
or breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage.?.This book is useful for researchers in the fields of genomics, genetics, computational biology and bioin978-981-16-5995-9978-981-16-5993-5
12#
發(fā)表于 2025-3-23 17:37:03 | 只看該作者
M. A. Sundaramahalingam,Ritika Kabra,Shailza Singh
13#
發(fā)表于 2025-3-23 18:27:40 | 只看該作者
14#
發(fā)表于 2025-3-23 23:44:01 | 只看該作者
Sudipto Bhattacharjee,Abhirupa Ghosh,Banani Saha,Sudipto Saha
15#
發(fā)表于 2025-3-24 03:35:33 | 只看該作者
16#
發(fā)表于 2025-3-24 08:55:29 | 只看該作者
17#
發(fā)表于 2025-3-24 11:58:17 | 只看該作者
Construction of Feedforward Multilayer Perceptron Model for Diagnosing Leishmaniasis Using Transcrignosing model for leishmaniasis, using transcriptome data. It was created using a recurrent neural network. The cognitive model of the trained network was interpreted using the maps and mathematical formula of the influencing parameters. The credit of the system was measured using the accuracy, loss
18#
發(fā)表于 2025-3-24 17:26:15 | 只看該作者
Big Data in Drug Discovery,proprietary and commercial screening platforms with the help of big data analysis and management. Thus, the importance of screening platforms and their success stories are highlighted with case studies. Overall, the integration of big data with AI-based tools greatly improves the efficiency of the d
19#
發(fā)表于 2025-3-24 19:56:54 | 只看該作者
An Overview of Databases and Tools for lncRNA Genomics Advancing Precision Medicine,lncRNA prediction, numerous computational repositories and predictive algorithms have been published in order to expand our horizons of the understanding and functions of lncRNAs. In this chapter, we described the current tools and computational repositories in the area of lncRNA biology covering nu
20#
發(fā)表于 2025-3-24 23:54:15 | 只看該作者
How Machine Learning Has Revolutionized the Field of Cancer Informatics?,iction of survival rate to the estimation of cancer recurrence, machine learning methods have been proved to provide hopefulness to the scientific community. In the chapter, we discuss machine learning applications in cancer research in various prospects like cancer detection/diagnosis, prognosis, s
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