M
Mohammed Gollapalli
Researcher at University of Dammam
Publications - 44
Citations - 522
Mohammed Gollapalli is an academic researcher from University of Dammam. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 9, co-authored 24 publications receiving 198 citations. Previous affiliations of Mohammed Gollapalli include Information Technology University & University of Queensland.
Papers
More filters
Journal ArticleDOI
Supervised Machine Learning Empowered Multifactorial Genetic Inheritance Disorder Prediction
Taher M. Ghazal,Hussam Al Hamadi,Muhammad Umar Nasir,Atta-ur-Rahman,Mohammed Gollapalli,Muhammad Zubair,Muhammad Adnan Khan,Chan Yeob Yeun +7 more
TL;DR: The proposed SVM-based dementia, cancer, and diabetes from multifactorial genetic inheritance disorder prediction (MGIDP) give attractive results as compared with the proposed model of KNN, which plays a vital role to minimize the death ratio around the world.
Journal ArticleDOI
Synthesis of benzothiazole derivatives as a potent α-glucosidase inhibitor.
Mohammed Gollapalli,Muhammad Taha,Muhammad Javid,Noor B. Almandil,Fazal Rahim,Abdul Wadood,Ashik Mosaddik,Mohamed Ibrahim,Mohammed A. Alqahtani,Yasser A. Bamarouf +9 more
TL;DR: This work has synthesized benzothiazole based oxadiazole in search of potent anti-diabetic agent as α-glucosidase Inhibitors and structure activity relationship has been established for all compounds.
Journal ArticleDOI
Synthesis of Bis-indolylmethane sulfonohydrazides derivatives as potent α-Glucosidase inhibitors.
Mohammed Gollapalli,Muhammad Taha,Hayat Ullah,Muhammad Nawaz,Laode Muhammad Ramadhan AlMuqarrabun,Fazal Rahim,Faiza Qureshi,Ashik Mosaddik,Norizan Ahmat,Khalid Mohammed Khan,Khalid Mohammed Khan +10 more
TL;DR: All the active bis-indolylmethane sulfonohydrazides derivatives showed considerable binding interactions within the active site (acarbose inhibition site) of α-glucosidase, and none of them are toxic.
Journal ArticleDOI
Synthesis, in vitro urease inhibitory potential and molecular docking study of Benzimidazole analogues
Khalid Zaman,Fazal Rahim,Muhammad Taha,Hayat Ullah,Abdul Wadood,Mohsan Nawaz,Fahad Khan,Zainul Wahab,Syed Adnan Ali Shah,Ashfaq Ur Rehman,Abdel-Nasser Kawde,Mohammed Gollapalli +11 more
TL;DR: In order to rationalize the binding interactions of most active compounds with the active site of urease enzyme, molecular docking study was conducted and suggested that the variations in the inhibitory potentials of the analogues are the result of different substitutions on phenyl ring.
Journal ArticleDOI
Rainfall Prediction System Using Machine Learning Fusion for Smart Cities
Atta-ur-Rahman,Sagheer Abbas,Mohammed Gollapalli,Rashad Ahmed,Shabib Aftab,Munir Uddin Ahmad,Muhammad Adnan Khan,Amir Mosavi +7 more
TL;DR: In this article , the authors proposed a real-time rainfall prediction system for smart cities using a machine learning fusion technique, which uses four widely used supervised machine learning techniques, i.e., decision tree, Naïve Bayes, K-nearest neighbors, and support vector machines.