Cédric Arisdakessian

Author

University of Hawaiʻi at Mānoa ORCID

Also Known As

Arisdakessian, Cedric, Cedric Arisdakessian, Cédric Arisdakessian, Cédric G Arisdakessian

Publications

650

Citations

H-Index

Concepts

All Affiliations

University of Hawaiʻi at Mānoa University of Hawaii System University of Hawaii Cancer Center Cancer Center of Hawaii University of Michigan

About

Cédric Arisdakessian is an author at University of Hawaiʻi at Mānoa specializing in bioinformatics, computational biology, and systems biology.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	3	3	116
2	Medicine	3	3	116
3	Cell Biology	2	2	85
4	Data Science	1	1	28
5	Microbiology	1	1	31

Cédric Arisdakessian

Publications

642

Citations

H-Index

Page 1

	Year	Citations
DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Genome biology	2019	307
Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists Xun Zhu, Thomas Wolfgruber, Austin Tasato, Genome Medicine	2017	87
The amphibian microbiome exhibits poor resilience following pathogen-induced disturbance Andrea J. Jani, Jessie Bushell, Cédric Arisdakessian, The ISME Journal	2021	84
Evaluation of STAR and Kallisto on Single Cell RNA-Seq Data Alignment Yuheng Du, Qianhui Huang, Cédric Arisdakessian, G3 Genes Genomes Genetics EngineeringGeneticsTranscriptomics TechnologyGenomicsSequence Alignment	2020	57
MetaFlow\|mics: Scalable and Reproducible Nextflow Pipelines for the Analysis of Microbiome Marker Data Cédric Arisdakessian, Sean B. Cleveland, Mahdi Belcaid Practice and Experience in Advanced Research Computing DysbiosisEngineeringBioinformatics DatabaseComprehensive PipelineHigh Throughput Sequencing	2020	31
DeepImpute: an accurate, fast and scalable deep neural network method to impute single-cell RNA-Seq data Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Present DeepimputeMachine LearningEngineeringGeneticsSingle-cell Rna-seq Data	2018	28
CoCoNet: an efficient deep learning tool for viral metagenome binning Cédric Arisdakessian, Olivia D. Nigro, Grieg F. Steward, Bioinformatics	2021	25
Pan-cancer multi-omic model of LINE-1 activity reveals locus heterogeneity of retrotransposition efficiency Alexander Solovyov, Julie M. Behr, David Hoyos, Nature Communications	2025	12
GranatumX: A Community-Engaging, Modularized, and Flexible Webtool for Single-Cell Data Analysis David Garmire, Xun Zhu, Aravind Mantravadi, Genomics Proteomics & Bioinformatics	2021	11

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