Spike2vec: An efficient and scalable embedding approach for covid-19 spike sequences
S Ali, M Patterson - 2021 IEEE International Conference on Big …, 2021 - ieeexplore.ieee.org
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 …
becoming available, including genomic sequence data. The total number of genomic …
A k-mer Based Approach for SARS-CoV-2 Variant Identification
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 …
continuous mutation, it is of pivotal importance to design a system to identify different known …
[HTML][HTML] Benchmarking machine learning robustness in COVID-19 genome sequence classification
The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of
sequence data of the SARS-CoV-2 genome—millions of sequences and counting. This …
sequence data of the SARS-CoV-2 genome—millions of sequences and counting. This …
Effective and scalable clustering of SARS-CoV-2 sequences
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 …
evolutionary process. Unlike any other virus, the number of currently available sequences of …
[HTML][HTML] Robust representation and efficient feature selection allows for effective clustering of sars-cov-2 variants
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 …
a result of the COVID-19 pandemic, has created an opportunity for researchers to analyze …
Predicting attributes of nodes using network structure
In many graphs such as social networks, nodes have associated attributes representing their
behavior. Predicting node attributes in such graphs is an important task with applications in …
behavior. Predicting node attributes in such graphs is an important task with applications in …
Efficient approximate kernel based spike sequence classification
Machine learning (ML) models, such as SVM, for tasks like classification and clustering of
sequences, require a definition of distance/similarity between pairs of sequences. Several …
sequences, require a definition of distance/similarity between pairs of sequences. Several …
Effect of analysis window and feature selection on classification of hand movements using EMG signal
Electromyography (EMG) signals have been successfully employed for driving prosthetic
limbs of a single or double degree of freedom. This principle works by using the amplitude of …
limbs of a single or double degree of freedom. This principle works by using the amplitude of …
Efficient approximation algorithms for strings kernel based sequence classification
Sequence classification algorithms, such as SVM, require a definition of distance (similarity)
measure between two sequences. A commonly used notion of similarity is the number of …
measure between two sequences. A commonly used notion of similarity is the number of …
Clustering sars-cov-2 variants from raw high-throughput sequencing reads data
The massive amount of genomic data appearing over the past two years for SARS-CoV-2
has challenged traditional methods for studying the dynamics of the COVID-19 pandemic …
has challenged traditional methods for studying the dynamics of the COVID-19 pandemic …