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Calvin Cicha

Researcher at Montana State University

Publications -  6
Citations -  475

Calvin Cicha is an academic researcher from Montana State University. The author has contributed to research in topics: Genome & Mutant. The author has an hindex of 4, co-authored 6 publications receiving 261 citations. Previous affiliations of Calvin Cicha include University of Minnesota.

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Journal ArticleDOI

Temporal Detection and Phylogenetic Assessment of SARS-CoV-2 in Municipal Wastewater.

TL;DR: It is shown that changes in SARS-CoV-2 RNA concentrations follow symptom onset gathered by retrospective interview of patients but precedes clinical test results, and how genome sequencing can be used for genotyping viral strains circulating in a community.
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SARS-CoV-2 genomic surveillance identifies naturally occurring truncation of ORF7a that limits immune suppression.

TL;DR: Using global phylogenomics, this article showed that mutations frequently occur in the C-terminal end of ORF7a, which negates anti-immune activities of the protein, which results in elevated type I interferon response to the viral infection.
Posted ContentDOI

SARS-CoV-2 genomic surveillance identifies naturally occurring truncations of ORF7a that limit immune suppression

TL;DR: In this article, the C-terminal truncation of ORF7a has been shown to result in distinct changes in interferon stimulated gene expression, and these changes affect viral mechanisms responsible for suppressing the immune response.
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Intrinsic Signal Amplification by Type-III CRISPR-Cas Systems Provides a Sequence-Specific SARS-CoV-2 Diagnostic

TL;DR: In this article, the type III CRISPR-Cas system was used for sensitive and sequence-specific detection of SARS-CoV-2 genomes using a two-pot reaction consisting of RT-LAMP and T7-transcription.
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Complete Genome Sequence of Brucella abortus Phage EF4, Determined Using Long-Read Sequencing.

TL;DR: Brucellaphage EF4 was isolated from elk feces and displays nucleotide similarity to other brucellaphages of the genus Perisivirus, which is predicted to contain 72 coding regions, 38 of which have been assigned predicted functions.