Author

Naihui Zhou

Iowa State UniversityORCID 0000-0001-6268-6149Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Research Focus:benchmarking· 2 Organism:Drosophila· 2 Approach:Bayesian inference· 1 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Balint Z KacsohiD· 2 shared Iddo FriedbergiD· 2 shared Yuxiang JiangiD· 2 shared Ahmet Süreyya RifaioğluiD· 1 shared Alan J. MedlariD· 1 shared Alberto PaccanaroiD· 1 shared Alessandro PetriniiD· 1 shared Alex Alves FreitasiD· 1 shared

Activity by Year

2018-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Balint Z KacsohORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintDec 16, 2019

Hierarchical Markov Random Field model captures spatial dependency in gene expression, demonstrating regulation via the 3D genome

Naihui Zhou, Iddo Friedberg, Mark S. Kaiser

The paper introduces a model to quantify spatial dependency in gene expression using HiC and RNA-seq data, finding strong intra- and inter-chromosomal spatial correlations.

3 citations

humanHi-C

𝕏 PostBluesky

BioinformaticsGenome biologyPeer-reviewedNov 19, 2019

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Naihui Zhou, Yuxiang Jiang, Timothy R. Bergquist…·Enrico Lavezzo

The paper reports results from the CAFA3 challenge, showing improved computational protein function prediction and new annotations for over 1000 genes through experimental screens in C. albicans, P. aureginosa, and Drosophila.

452 citationstop 1%

C. elegansDrosophila

𝕏 PostBluesky

NeuroscienceG3 Genes Genomes GeneticsPeer-reviewedNov 22, 2018

New Drosophila long-term memory genes revealed by assessing computational function prediction methods.

Balint Z Kacsoh, Stephen Barton, Yuxiang Jiang…·Giovanni Bosco

The paper identifies 11 novel Drosophila genes involved in long-term memory formation using computational methods and behavioral assays.

23 citations

Drosophilastatistical model

𝕏 PostBluesky