4 citations · 5 across the 7 of their papers we have counts for
5 papers · 1 filter
Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants
Zahra Tayebi, Sarwan Ali, Murray Patterson
The widespread availability of large amounts of genomic data on the SARS-CoV-2 virus, as a result of the COVID-19 pandemic, has created an opportunity for researchers to analyze th…
Efficient Analysis of COVID-19 Clinical Data using Machine Learning Models
Sarwan Ali, Yijing Zhou, Murray Patterson
Because of the rapid spread of COVID-19 to almost every part of the globe, huge volumes of data and case studies have been made available, providing researchers with a unique oppor…
Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequences
Sarwan Ali, Murray Patterson
With the rapid global spread of COVID-19, more and more data related to this virus is becoming available, including genomic sequence data. The total number of genomic sequences tha…
Effective and scalable clustering of SARS-CoV-2 sequences
Sarwan Ali, Tamkanat-E-Ali, Muhammad Asad Khan +2
SARS-CoV-2, like any other virus, continues to mutate as it spreads, according to an evolutionary process. Unlike any other virus, the number of currently available sequences of SA…
A k-mer Based Approach for SARS-CoV-2 Variant Identification
Sarwan Ali, Bikram Sahoo, Naimat Ullah +3
With the rapid spread of the novel coronavirus (COVID-19) across the globe and its continuous mutation, it is of pivotal importance to design a system to identify different known (…