5 citations · 12 across the 35 of their papers we have counts for
10 papers · 1 filter
Sequence-Based Nanobody-Antigen Binding Prediction
Usama Sardar, Sarwan Ali, Muhammad Sohaib Ayub +4
Nanobodies (Nb) are monomeric heavy-chain fragments derived from heavy-chain only antibodies naturally found in Camelids and Sharks. Their considerably small size (~3-4 nm; 13 kDa)…
Robust Brain Age Estimation via Regression Models and MRI-derived Features
Mansoor Ahmed, Usama Sardar, Sarwan Ali +3
The determination of biological brain age is a crucial biomarker in the assessment of neurological disorders and understanding of the morphological changes that occur during aging.…
Virus2Vec: Viral Sequence Classification Using Machine Learning
Sarwan Ali, Babatunde Bello, Prakash Chourasia +4
Understanding the host-specificity of different families of viruses sheds light on the origin of, e.g., SARS-CoV-2, rabies, and other such zoonotic pathogens in humans. It enables…
PCD2Vec: A Poisson Correction Distance-Based Approach for Viral Host Classification
Sarwan Ali, Taslim Murad, Murray Patterson
Coronaviruses are membrane-enveloped, non-segmented positive-strand RNA viruses belonging to the Coronaviridae family. Various animal species, mainly mammalian and avian, are sever…
ViralVectors: Compact and Scalable Alignment-free Virome Feature Generation
Sarwan Ali, Prakash Chourasia, Zahra Tayebi +2
The amount of sequencing data for SARS-CoV-2 is several orders of magnitude larger than any virus. This will continue to grow geometrically for SARS-CoV-2, and other viruses, as ma…
T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification
Zahra Tayebi, Sarwan Ali, Prakash Chourasia +2
Cancer is a complex disease characterized by uncontrolled cell growth and proliferation. T cell receptors (TCRs) are essential proteins for the adaptive immune system, and their sp…
BioSequence2Vec: Efficient Embedding Generation For Biological Sequences
Sarwan Ali, Usama Sardar, Murray Patterson +1
Representation learning is an important step in the machine learning pipeline. Given the current biological sequencing data volume, learning an explicit representation is prohibiti…
Exploring The Potential Of GANs In Biological Sequence Analysis
Taslim Murad, Sarwan Ali, Murray Patterson
Biological sequence analysis is an essential step toward building a deeper understanding of the underlying functions, structures, and behaviors of the sequences. It can help in ide…
Efficient Classification of SARS-CoV-2 Spike Sequences Using Federated Learning
Prakash Chourasia, Taslim Murad, Zahra Tayebi +3
This paper presents a federated learning (FL) approach to train an AI model for SARS-Cov-2 variant classification. We analyze the SARS-CoV-2 spike sequences in a distributed way, w…
Anderson Acceleration For Bioinformatics-Based Machine Learning
Sarwan Ali, Prakash Chourasia, Murray Patterson
Anderson acceleration (AA) is a well-known method for accelerating the convergence of iterative algorithms, with applications in various fields including deep learning and optimiza…