Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence
Classification

Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence Classification

18 July 2022

Sarwan Ali

Alexander Zelikovskiy

Murray Patterson

Papers citing "Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence Classification"

7 / 7 papers shown

Title
Virus2Vec: Viral Sequence Classification Using Machine Learning Sarwan Ali B. Bello Prakash Chourasia Ria Thazhe Punathil Pin-Yu Chen Imdadullah Khan Murray Patterson 32 2 0 24 Apr 2023
ViralVectors: Compact and Scalable Alignment-free Virome Feature Generation Sarwan Ali Prakash Chourasia Z. Tayebi B. Bello Murray Patterson 27 6 0 06 Apr 2023
BioSequence2Vec: Efficient Embedding Generation For Biological Sequences Sarwan Ali Usama Sardar Murray Patterson Imdadullah Khan 23 1 0 01 Apr 2023
Optimal Extended Neighbourhood Rule $k$ Nearest Neighbours Ensemble Amjad Ali Zardad Khan Dost Muhammad Khan Saeed Aldahmani 21 0 0 21 Nov 2022
Evaluating COVID-19 Sequence Data Using Nearest-Neighbors Based Network Model Sarwan Ali 16 5 0 19 Nov 2022
Efficient Approximate Kernel Based Spike Sequence Classification Sarwan Ali Bikram Sahoo Muhammad Asad Khan A. Zelikovsky Imdadullah Khan Murray Patterson AI4TS 33 22 0 11 Sep 2022
A k-mer Based Approach for SARS-CoV-2 Variant Identification Sarwan Ali Bikram Sahoo N. Ullah Alexander Zelikovskiy M. Patterson Imdadullah Khan 59 39 0 07 Aug 2021