A Novel Feature Extraction Approach for the Clustering and Classification of Genome Sequences-Reference-Cited by-同舟云学术

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A Novel Feature Extraction Approach for the Clustering and Classification of Genome Sequences

Published:2023-12-05 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Symposium Series on Computational Intelligence (SSCI)
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Author:

Dwivedi Rajesh¹,Tiwari Aruna¹,Bharill Neha²,Ratnaparkhe Milind³,Tripathi Abhishek¹,Jha Preeti⁴

Affiliation:

1. Indian Institute of Technology,Dept. of Computer Science and Engg.,Indore

2. Mahindra University,Dept. of Computer Science and Engg.,Hyderabad

3. ICAR-IISR,Dept. of Biotechnology,Indore

4. Koneru Lakshmaiah Education Foundation Bowrampet,Hyderabad,India

Funder

Council of Scientific and Industrial Research (CSIR), Government of India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10371778/10371788/10372047.pdf?arnumber=10372047

Reference19 articles.

1. A novel apache spark-based 14-dimensional scalable feature extraction approach for the clustering of genomics data

2. Metagenomic approach studying the taxonomic and functional diversity of the bacterial community in a mesotrophic lake (Lac du Bourget - France)

3. Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis

4. Deep Learning for Taxonomic Classification of Biological Bacterial Sequences

5. A novel feature extraction method based on highly expressed SNPs for tissue-specific gene prediction

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A taxonomy of unsupervised feature selection methods including their pros, cons, and challenges;The Journal of Supercomputing;2024-07-22

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