Eglė Godliauskaitė

ORCID: 0009-0001-7804-5431
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About
Contact & Profiles
Research Areas
  • Machine Learning in Bioinformatics
  • Protein Structure and Dynamics
  • RNA and protein synthesis mechanisms
  • Fungal Biology and Applications
  • Microbial Natural Products and Biosynthesis
  • Plant Virus Research Studies
  • Advanced biosensing and bioanalysis techniques
  • Epigenetics and DNA Methylation
  • Enzyme-mediated dye degradation
  • CRISPR and Genetic Engineering
  • Gut microbiota and health
  • RNA modifications and cancer
  • Plant Pathogens and Fungal Diseases

Vilnius University
2022

Abstract Motivation Reliable prediction of protein thermostability from its sequence is valuable for both academic and industrial research. This problem can be tackled using machine learning by taking advantage the recent blossoming deep methods analysis. These facilitate training on more data and, possibly, enable development versatile predictors multiple ranges temperatures. Results We applied principle transfer to predict embeddings generated language models (pLMs) an input sequence. used...

10.1093/bioinformatics/btae157 article EN cc-by Bioinformatics 2024-03-18

Article21 October 2022Open Access Source DataTransparent process A new family of CRISPR-type V nucleases with C-rich PAM recognition Tomas Urbaitis CasZyme, Vilnius, Lithuania Institute Biotechnology, Vilnius University, Contribution: Conceptualization, Data curation, Formal analysis, Validation, ​Investigation, Visualization, Methodology, Writing - original draft, review & editing Search for more papers by this author Giedrius Gasiunas Corresponding Author [email protected]...

10.15252/embr.202255481 article EN cc-by EMBO Reports 2022-10-21

Abstract Motivation Reliable prediction of protein thermostability from its sequence is valuable for both academic and industrial research. This problem can be tackled using machine learning by taking advantage the recent blossoming deep methods analysis. These facilitate training on more data and, possibly, enable development versatile predictors multiple ranges temperatures. Results We applied principle transfer to predict embeddings generated language models (pLMs) an input sequence. used...

10.1101/2023.03.27.534365 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2023-03-28

The formation of three oxidative DNA 5-methylcytosine (5mC) modifications (oxi-mCs)—5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC)—by the TET/JBP family dioxygenases prompted intensive studies their functional roles in mammalian cells. However, interplay these less abundant modified nucleotides other eukaryotic lineages remains poorly understood. We carried out a systematic study content distribution oxi-mCs RNA basidiomycetes Laccaria bicolor...

10.1098/rsob.210302 article EN cc-by Open Biology 2022-03-01
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