Muhammad Arif

Orcid: 0000-0003-3950-6618

Affiliations:
  • Nanjing University of Science and Technology, Department of computer science and technology, China (PhD 2021)
  • University of Management and Technology, Department of Informatics and Systems, School of Systems and Technology, Lahore, Pakistan


According to our database1, Muhammad Arif authored at least 12 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
DPI_CDF: druggable protein identifier using cascade deep forest.
BMC Bioinform., December, 2024

Differential Methylation Analysis in Normal Breast Tissue Contralateral to Tumour Reveals PROM1 As a Potential Prognostic Biomarker.
Proceedings of the 2024 8th International Conference on Medical and Health Informatics, 2024

In Silico Analysis of Pathogenic Missense Mutation in GBA protein for Gaucher Disease.
Proceedings of the 2024 8th International Conference on Medical and Health Informatics, 2024

2023
MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction.
J. Chem. Inf. Model., November, 2023

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images.
Eng. Appl. Artif. Intell., November, 2023

Improving DNA-Binding Protein Prediction Using Three-Part Sequence-Order Feature Extraction and a Deep Neural Network Algorithm.
J. Chem. Inf. Model., February, 2023

VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants.
Briefings Bioinform., January, 2023

Augmented Reality and its Applications in Education: A Systematic Survey.
IEEE Access, 2023

2022
DeepCPPred: A Deep Learning Framework for the Discrimination of Cell-Penetrating Peptides and Their Uptake Efficiencies.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion.
Briefings Bioinform., 2022

2020
TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree.
J. Comput. Aided Mol. Des., 2020

2018
Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine.
Int. J. Data Min. Bioinform., 2018


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