7 papers
Multi-Scale Reversible Chaos Game Representation: A Unified Framework for Sequence Classification
Sarwan Ali, Taslim Murad
Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Chaos Game Representation (MS-…
Murmur2Vec: A Hashing Based Solution For Embedding Generation Of COVID-19 Spike Sequences
Sarwan Ali, Taslim Murad
Early detection and characterization of coronavirus disease (COVID-19), caused by SARS-CoV-2, remain critical for effective clinical response and public-health planning. The global…
Sequence-to-Image Transformation for Sequence Classification Using Rips Complex Construction and Chaos Game Representation
Sarwan Ali, Taslim Murad, Imdadullah Khan
Traditional feature engineering approaches for molecular sequence classification suffer from sparsity issues and computational complexity, while deep learning models often underper…
DANCE: Deep Learning-Assisted Analysis of Protein Sequences Using Chaos Enhanced Kaleidoscopic Images
Taslim Murad, Prakash Chourasia, Sarwan Ali +2
Cancer is a complex disease characterized by uncontrolled cell growth. T cell receptors (TCRs), crucial proteins in the immune system, play a key role in recognizing antigens, incl…
Sequence Analysis Using the Bezier Curve
Taslim Murad, Sarwan Ali, Murray Patterson
The analysis of sequences (e.g., protein, DNA, and SMILES string) is essential for disease diagnosis, biomaterial engineering, genetic engineering, and drug discovery domains. Conv…
Neuromorphic Spiking Neural Network Based Classification of COVID-19 Spike Sequences
Taslim Murad, Prakash Chourasia, Sarwan Ali +2
The availability of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus data post-COVID has reached exponentially to an enormous magnitude, opening research doors to…