Protein Redesign and Engineering Using Machine Learning (English)
- New search for: Basit, Zhuha
- New search for: Akram, Hira
- New search for: Iqbal, Muhammad Mudassir
- New search for: Muhammad, Gulzar
- New search for: Aslam, Muhammad Shahbaz
- New search for: Gul, Iram
- New search for: Jamil, Muhammad
- New search for: Tahir, Mudassir Hussain
- New search for: Inamuddin
- New search for: Altalhi, Tariq
- New search for: Cruz, Jorddy N.
- New search for: Refat, Moamen Salah El‐Deen
- New search for: Basit, Zhuha
- New search for: Akram, Hira
- New search for: Iqbal, Muhammad Mudassir
- New search for: Muhammad, Gulzar
- New search for: Aslam, Muhammad Shahbaz
- New search for: Gul, Iram
- New search for: Jamil, Muhammad
- New search for: Tahir, Mudassir Hussain
In:
Drug Design Using Machine Learning
;
247-282
;
2022
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ISBN:
- Article/Chapter (Book) / Electronic Resource
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Title:Protein Redesign and Engineering Using Machine Learning
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Contributors:Inamuddin ( editor ) / Altalhi, Tariq ( editor ) / Cruz, Jorddy N. ( editor ) / Refat, Moamen Salah El‐Deen ( editor ) / Basit, Zhuha ( author ) / Akram, Hira ( author ) / Iqbal, Muhammad Mudassir ( author ) / Muhammad, Gulzar ( author ) / Aslam, Muhammad Shahbaz ( author ) / Gul, Iram ( author )
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Published in:Drug Design Using Machine Learning ; 247-282
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Publisher:
- New search for: John Wiley & Sons, Inc.
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Place of publication:Hoboken, NJ, USA
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Publication date:2022-10-10
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Size:36 pages
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ISBN:
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DOI:
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Type of media:Article/Chapter (Book)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents eBook
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Molecular Recognition and Machine Learning to Predict Protein‐Ligand InteractionsReyes Chaparro, A. / Moreno‐Melendres, J.A. / Ramos‐Jacques, A.L. / Hernandez‐Martinez, A.R. et al. | 2022
- 21
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Machine Learning Approaches to Improve Prediction of Target‐Drug InteractionsBalatti, Galo, E. / Barletta, Patricio, G. / Perez, Andres, D. / Giudicessi, Silvana, L. / Martínez‐Ceron, María, C. et al. | 2022
- 97
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Machine Learning Applications in Rational Drug DiscoveryChugh, Hemanshi / Singh, Sonal et al. | 2022
- 117
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Deep Learning for the Selection of Multiple AnalogsDeepa, C. / Balaji, D. / Bhuvaneswari, V. / Rajeshkumar, L. / Ramesh, M. / Priyadharshini, M. et al. | 2022
- 143
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Drug Repurposing Based on Machine LearningTripathi, Laxmi / Kumar, Praveen / Swain, Kalpana / Pattnaik, Satyanarayan et al. | 2022
- 165
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Recent Advances in Drug Design With Machine LearningFaisal, Muhammad et al. | 2022
- 195
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Loading of Drugs in Biodegradable Polymers Using Supercritical Fluid TechnologyDíaz, Janet de los Angeles Chinellato / Bordín, Santiago Fernandez / Mattea, Facundo / Romero, Marcelo Ricardo et al. | 2022
- 225
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Neural Network for Screening Active Sites on ProteinsBustamante‐Torres, Johanna / Pardo, Samantha / Bustamante‐Torres, Moises et al. | 2022
- 247
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Protein Redesign and Engineering Using Machine LearningBasit, Zhuha / Akram, Hira / Iqbal, Muhammad Mudassir / Muhammad, Gulzar / Aslam, Muhammad Shahbaz / Gul, Iram / Jamil, Muhammad / Tahir, Mudassir Hussain et al. | 2022
- 283
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Role of Transcriptomics and Artificial Intelligence Approaches for the Selection of Bioactive CompoundsZameer, Roshan / Tariq, Sana / Noreen, Sana / Sadaqat, Muhammad / Azeem, Farrukh et al. | 2022
- 319
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Prediction of Drug Toxicity Through Machine LearningGharabeiki, Ariga / Monemian, Foad / Kargari, Ali et al. | 2022
- 339
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Artificial Intelligence for Assessing Side EffectsPanchbhai, Aarati et al. | 2022
- 351
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Index| 2022
- i
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Front Matter| 2022