This book provides readers a comprehensive understanding of the application of machine Learning and deep Learning in proteomics, genomics, microarrays, text mining and related fields. The key objective is to provide machine learning applications to biological science problems, focusing on problems related to bioinformatics.
This book provides readers a comprehensive understanding of the application of machine Learning and deep Learning in proteomics, genomics, microarrays, text mining and related fields. The key objective is to provide machine learning applications to biological science problems, focusing on problems related to bioinformatics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Faheem Syeed Masoodi is Assistant Professor in the Department of Computer Science, University of Kashmir, India. Dr. Mohammad Tabrez Quasim is Assistant Professor at University of Bisha, Saudi Arabia. Dr. Syed Nisar Hussain Bukhari is a Scientist-C at the National Institute of Electronics and Information Technology (NIELIT) J&K, Srinagar, India. Prof. Dr. Sarvottam Dixit holds the post of Advisor to The Chairperson, Mewar University, Chittorgarh, India. Dr. Shadab Alam is currently Assistant Professor in the Department of Computer Science, Jazan University, Jazan, Saudi Arabia.
Inhaltsangabe
1. Deep Learning Approaches, Algorithms, and Applications in Bioinformatics. 2. Role of Artificial Intelligence and Machine Learning in Schizophrenia - A Survey. 3. Understanding Financial Impact of Machine Learning and Deep Learning in Healthcare: An Analysis 4. Face Mask Detection Alert System for COVID Prevention Using Deep Learning. 5. An XGBoost-Based Classification Method to Classify Breast Cancer. 6. Prediction of Erythemato-Squamous Diseases Using Machine Learning. 7. Grouping of Mushroom 5.8s rRNA Sequences by Implementing Hierarchical Clustering Algorithm. 8. Applications of Machine Learning and Deep Learning in Genomics and Proteomics. 9. Artificial Intelligence: For Biological Data. 10. Application of ML and DL on Biological Data. 11. Deep Learning for Bioinformatics.
1. Deep Learning Approaches, Algorithms, and Applications in Bioinformatics. 2. Role of Artificial Intelligence and Machine Learning in Schizophrenia - A Survey. 3. Understanding Financial Impact of Machine Learning and Deep Learning in Healthcare: An Analysis 4. Face Mask Detection Alert System for COVID Prevention Using Deep Learning. 5. An XGBoost-Based Classification Method to Classify Breast Cancer. 6. Prediction of Erythemato-Squamous Diseases Using Machine Learning. 7. Grouping of Mushroom 5.8s rRNA Sequences by Implementing Hierarchical Clustering Algorithm. 8. Applications of Machine Learning and Deep Learning in Genomics and Proteomics. 9. Artificial Intelligence: For Biological Data. 10. Application of ML and DL on Biological Data. 11. Deep Learning for Bioinformatics.
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