User profiles for Z. Chervontseva
Zoe ChervontsevaUniversity of Hamburg Verified email at uni-hamburg.de Cited by 95 |
Translation at first sight: the influence of leading codons
IA Osterman, ZS Chervontseva… - Nucleic Acids …, 2020 - academic.oup.com
First triplets of mRNA coding region affect the yield of translation. We have applied the flowseq
method to analyze >30 000 variants of the codons 2–11 of the fluorescent protein reporter …
method to analyze >30 000 variants of the codons 2–11 of the fluorescent protein reporter …
Influence of the spacer region between the Shine–Dalgarno box and the start codon for fine‐tuning of the translation efficiency in Escherichia coli
ES Komarova, ZS Chervontseva… - Microbial …, 2020 - Wiley Online Library
Translation efficiency contributes several orders of magnitude difference in the overall yield
of exogenous gene expression in bacteria. In diverse bacteria, the translation initiation site, …
of exogenous gene expression in bacteria. In diverse bacteria, the translation initiation site, …
[HTML][HTML] Adaptive evolution at mRNA editing sites in soft-bodied cephalopods
… Z-score values obtained by the RNASurface program (Soldatov, Vinogradova & Mironov,
2013). Here, Z-score of a sequence is defined as Z = … the best (minimal) Z-score of all structured …
2013). Here, Z-score of a sequence is defined as Z = … the best (minimal) Z-score of all structured …
Reprograming of sRNA target specificity by the leader peptide peTrpL in response to antibiotic exposure
Trans-acting regulatory RNAs have the capacity to base pair with more mRNAs than generally
detected under defined conditions, raising the possibility that sRNA target specificities …
detected under defined conditions, raising the possibility that sRNA target specificities …
Identification of differentially expressed gene modules in heterogeneous diseases
…, OI Isaeva, Z Chervontseva… - …, 2021 - academic.oup.com
Motivation Identification of differentially expressed genes is necessary for unraveling disease
pathogenesis. This task is complicated by the fact that many diseases are heterogeneous …
pathogenesis. This task is complicated by the fact that many diseases are heterogeneous …
[HTML][HTML] A hierarchy in clusters of cephalopod mRNA editing sites
MA Moldovan, ZS Chervontseva, DS Nogina… - Scientific Reports, 2022 - nature.com
RNA editing in the form of substituting adenine with inosine (A-to-I editing) is the most frequent
type of RNA editing in many metazoan species. In most species, A-to-I editing sites tend …
type of RNA editing in many metazoan species. In most species, A-to-I editing sites tend …
[HTML][HTML] Predicting RNA secondary structure by a neural network: what features may be learned?
Deep learning is a class of machine learning techniques capable of creating internal
representation of data without explicit preprogramming. Hence, in addition to practical applications, …
representation of data without explicit preprogramming. Hence, in addition to practical applications, …
The bacterial leader peptide peTrpL has a conserved function in antibiotic-dependent posttranscriptional regulation of ribosomal genes
…, AR Varadarajan, K Baumgardt, Z Chervontseva… - bioRxiv, 2019 - biorxiv.org
The ribosome-dependent attenuator located upstream of bacterial tryptophan biosynthesis
genes harbors a small ORF trpL containing tryptophan codons. When tryptophan is available, …
genes harbors a small ORF trpL containing tryptophan codons. When tryptophan is available, …
[HTML][HTML] DESMOND 2.0: Identification of differentially expressed biclusters for unsupervised patient stratification
…, A Savchik, ZS Chervontseva… - …, 2022 - drugrepocentral.scienceopen.com
Unsupervised patient stratification based on omics data is traditionally approached by clustering
methods which may be inefficient for datasets with multiple patterns overlapping in rows …
methods which may be inefficient for datasets with multiple patterns overlapping in rows …
Features of nucleotide sequences learned by neural networks
Z Chervontseva - … технологии и системы 2019 (ИТиС 2019), 2019 - elibrary.ru
Neural networks are known to be good in generalising and discovery of novel non-trivial
patterns in complex data. Here we apply neural networks to several bioinformatic problems …
patterns in complex data. Here we apply neural networks to several bioinformatic problems …