Taslim Murad

Orcid: 0000-0001-6434-3297

According to our database1, Taslim Murad authored at least 15 papers between 2022 and 2024.

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

Timeline

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Bibliography

2024
PseAAC2Vec protein encoding for TCR protein sequence classification.
Comput. Biol. Medicine, March, 2024

Molecular sequence classification using efficient kernel based embedding.
Inf. Sci., 2024

Weighted Chaos Game Representation for Molecular Sequence Classification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

2023
Spike2CGR: an efficient method for spike sequence classification using chaos game representation.
Mach. Learn., October, 2023

Exploring The Potential Of GANs In Biological Sequence Analysis.
CoRR, 2023

Efficient Classification of SARS-CoV-2 Spike Sequences Using Federated Learning.
CoRR, 2023

Enhancing t-SNE Performance for Biological Sequencing Data Through Kernel Selection.
Proceedings of the Bioinformatics Research and Applications - 19th International Symposium, 2023

A New Direction in Membranolytic Anticancer Peptides classification: Combining Spaced k-mers with Chaos Game Representation.
Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

PCD2Vec: A Poisson Correction Distance Based Approach for Viral Host Classification.
Proceedings of the International Joint Conference on Neural Networks, 2023

T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification.
Proceedings of the Neural Information Processing - 30th International Conference, 2023

Circular Arc Length-Based Kernel Matrix For Protein Sequence Classification.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
DAO: Dynamic Adaptive Offloading for Video Analytics.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

PSSM2Vec: A Compact Alignment-Free Embedding Approach for Coronavirus Spike Sequence Classification.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

Spike2Signal: Classifying Coronavirus Spike Sequences with Deep Learning.
Proceedings of the Eighth IEEE International Conference on Big Data Computing Service and Applications, 2022

Hashing2Vec: Fast Embedding Generation for SARS-CoV-2 Spike Sequence Classification.
Proceedings of the Asian Conference on Machine Learning, 2022


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