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Special Issue "Comparative strength and potentials of quantitative structure-activity relationship and machine learning computational methods in material modeling and drug design"
The relationship between structural properties of chemical compounds and biological activities of many useful compounds and materials in drug discovery and design can be modeled with the aid of the quantitative structure-activity relationship (QSAR) computational method. The QSAR computational method involves generation of large number of potential descriptors which are subsequently tailored to a finite and reduced number necessary for fitting the best model within the QSAR description. However, the choice of appropriate and efficient descriptors might be challenging in implementing QSAR but the machine learning computational tools have shown superior potentials recently due to the intrinsic and uniqueness of machine learning methods in modeling material properties. Among the challenges of machine learning approaches include inability to generate empirical equations that can be easily implemented for future work. This special issue aims at hybridizing and comparing the potentials of QSAR and machine learning techniques in material modeling and drug design for specific applications. The following topics fall within the scope of this special issue
- Investigating the anticancer potentials of probable compounds using QSAR and machine learning computational methods
- Hybridization of machine learning techniques with population based optimization algorithm for enhancing materials’ properties during drug design
- Performance comparison of QSAR and machine learning computational methods for material modeling
- Molecular docking of the lead compounds with receptors’ active sites
- Pharmacokinetics studies of the lead compounds
- Molecular dynamic simulations of the lead compounds
Affiliation: Dr. Taoreed Owolabi, Physics and Electronics department, Adekunle Ajasin University, Akungba Akoko,Ondo State, Nigeria. Scopus link: Email: firstname.lastname@example.org Click here to view research profile of the lead editor
Profile: Dr. Taoreed O. Owolabi is a lecturer in the Department of Physics and Electronics, Adekunle Ajasin University, Akungba Akoko, Nigeria. He holds B.Sc degree in physics and Electronics from Adekunle Ajasin University. He obtained his M.Sc. and PhD degrees in Physics from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. He has participated in numerous research projects in KFUPM & Universiti Putra Malaysia (UPM) including those from Saudi ARAMCO oil and gas Company, making use of artificial intelligence based techniques in solving real industrial problems. His research interest revolves around application of machine learning algorithms for solving both classical and quantum condensed matter physical problems. He is an expert in material designs using advanced hybrid chemo-metrics. He has authored more than fifty peer-reviewed journal papers mostly indexed in Scopus and web of science. He also serves as reviewer for many leading journals He has presented papers in international conferences. He is a member of conference organizing committee in World Congress on Engineering and Computer Science, China (since 2016) View conference details and Regional Colloquium on Physics and Applications (CRePAs) 2020 View at the conference home page. He is serving as a guest editor for a special issue in the Journal of Nanomaterials published by Hindawi. He is presently an Editor of Journal of the Nigerian society of physical sciences as well as the journal of Mathematical problems in engineering.
Guest Editor 1
Affiliation: Professor Sunday Olatunji , College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. Email: email@example.com Click here to view research profile of the Guest Editor 2
Profile: Sunday Olusanya Olatunji (Aadam) is currently an Associate Professor in the College of Computer Science & IT, University of Dammam, Dammam, Saudi Arabia. He obtained his PhD in Computer Science from the Universiti Teknologi Malaysia (UTM) in 2012, bagging the best graduating Student Award Medal (PhD Computer Science). He received M.Sc. Degree in Computer Science, University of Ibadan, Nigeria in 2003. He obtained another M.Sc. Degree in Information and Computer Science, King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia in 2008 under the prestigious special Research Assistantship scholarship of KFUPM. He received the B.Sc. (Hons) Degree in Computer Science, Ondo State University (Now University of Ado Ekiti), Nigeria in 1999. His work experience in both University Teaching and Research span over 20 years. He has participated in numerous research projects in KFUPM & UTM including those from Saudi ARAMCO oil and gas Company, making use of artificial intelligence based techniques in solving real industrial problems. He has authored well over 100 publications as journal articles, books, and peer reviewed conferences proceedings, with Journals articles mostly in peer reviewed highly rated impact reputable SCOPUS and ISI journals. Not long ago, he was listed as one of the topmost researchers in the area of Artificial Intelligence in the Kingdom of Saudi Arabia based on the number of published papers in topmost Q1 journals (see the link below): https://twitter.com/dr_taisir/status/1170682686471585795?s=12 He is a member of IEEE, ACM, SPE, and Machine Intelligence Research Labs (USA). His research interests include artificial/computational intelligence, soft-computing, machine learning, Data Science and Data Mining with applications to different germane areas like oil, gas and energy modeling and predictions, biomedical predictions, software engineering metrics prediction, forensic investigation modeling, etc.
Guest Editor 2
Affiliation: Dr. Oluwatoba Emmanuel Oyeneyin, Theoretical and Computational Chemistry Unit, Department of Chemical Sciences, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria. Email: firstname.lastname@example.org Click here to view the profile of the Guest Editor 2
Profile: Dr Oluwatoba Emmanuel OYENEYIN is a Lecturer in the Department of Chemical Sciences, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria. He holds a B.Sc. (Ed.) in Chemistry from Adeyemi College of Education. He obtained his M.Sc. and PhD degrees from the University of Ibadan, Oyo State, Nigeria. His research interest is in the area of Theoretical and Computational materials design and Computer Aided Drug Design. He has authored more than thirty peer-reviewed journal papers. He is currently the Unit Head of Theoretical and Computational Chemistry Unit, Adekunle Ajasin University, Akungba-Akoko.
Guest Editor 3
Affiliation: Dr.Kabiru O Akande, Research Fellow - Conversational AI, Big Data, Enterprise and Artificial Intelligence Laboratory, Bristol Business School | University of the West of England, Frenchay Campus | Coldharbour Lane | Bristol | BS16 1QY, Telephone: 0117 32 86774 | Email: email@example.com Click here to view research profile of Guest Editor 3
Profile: Dr. Kabiru O. Akande is a machine learning engineer and research fellow at the University of the West of England (UWE). He obtained his first degree in Electronics and Electrical Engineering from Ladoke Akintola University of Technology (LAUTECH) and his MSc from King Fahd University of Petroleum and Minerals, Saudi Arabia. He proceeded to the University of Edinburgh where he bagged his PhD. His research interests cut across multiple disciplines including applications of artificial intelligence in petroleum reservoir characterization, material designs, communication channel modeling and air quality solutions. He has three US granted patents and has authored over 50 peer-reviewed Journal publications and conferences in leading publishing outlets including IEEE and many Q1 journals. He also serves as reviewer for many leading journals. He is a COREN certified Engineer and a registered member of the Nigerian society of Engineers (NSE).