Musfikur Rahaman Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
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Biography and Research Information
OverviewAI-generated summary
Musfikur Rahaman's research focuses on the intersection of machine learning and bioinformatics, with a particular emphasis on health-related applications. His work includes the development of computational approaches to analyze genetic data and identify disease associations. One publication details an integration of machine learning and bioinformatics to investigate the genetic effects of SARS-CoV-2 on idiopathic pulmonary fibrosis patients. Another publication explores pedagogical approaches to enhance learning outcomes in undergraduate computer science education. Rahaman has a total of two publications and has been cited 13 times, with an h-index of 2. He has collaborated with researchers at Arkansas Tech University, including Tolga Ensarı, Indira Kalyan Dutta, and Robin Ghosh, on shared publications.
Metrics
- h-index: 2
- Publications: 2
- Citations: 13
Selected Publications
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Enhancing the Programming Sequence for Undergraduate Computer Science Students: A Program for Improving Learning Outcomes (2023)
Collaboration Network
Top Collaborators
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
- Enhancing the Programming Sequence for Undergraduate Computer Science Students: A Program for Improving Learning Outcomes
- Enhancing the Programming Sequence for Undergraduate Computer Science Students: A Program for Improving Learning Outcomes
- Enhancing the Programming Sequence for Undergraduate Computer Science Students: A Program for Improving Learning Outcomes
- Enhancing the Programming Sequence for Undergraduate Computer Science Students: A Program for Improving Learning Outcomes
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