UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets-Reference-Cited by-同舟云学术

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UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets

Published:2023-12-05 Issue: Volume: Page:594-601
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Maitra Chayan¹,Seal Dibyendu B.²,Das Vivek³,Vorobeychik Yevgeniy⁴,De Rajat K.¹

Affiliation:

1. Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India

2. Deutsches Krebsforschungszentrum (DKFZ),Proteomics and Cancer Cell Signalling,Heidelberg,69120

3. Systems Biology and Target Discovery - Artificial Intelligence and Digital Research,Malov,Denmark

4. Washington University in St. Louis 1 Brookings Drive,Computer Science and Engineering,Saint Louis,MO,USA,63130

Funder

Indian Statistical Institute

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385731.pdf?arnumber=10385731

Reference17 articles.

1. Simultaneous epitope and transcriptome measurement in single cells

2. Multiplexed quantification of proteins and transcripts in single cells

3. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell

4. Joint profiling of chromatin accessibility and gene expression in thousands of single cells

5. SHARE-seq reveals chromatin potential

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