Publications by Galina V Orlova

Publications by authors named "Galina V Orlova"

J Integr Bioinform

December 2016

The study explores gene expression in the nervous system to understand the molecular and genetic basis for aggressive versus tolerant behaviors using grey rats specifically bred for these traits.
Researchers utilized advanced computer analysis to identify genes and gene regulation patterns associated with the different behaviors by examining brain samples from these genetically selected rats.
Findings revealed significant changes in gene expression, including differential splicing related to nerve impulse transmission and neuron development, emphasizing the importance of alternative splicing in influencing behavioral traits.

Nucleic Acids Res

January 2003

Analyzing gene regulatory networks is a complex challenge in postgenomic research, with a focus on transcription factor (TF) binding sites that can impact disease phenotypes.
The rSNP_Guide system helps predict these TF binding sites and has been validated by established connections between TF sites and diseases, as well as experimental data.
The tool identifies potential TF sites in similar genes based on known alterations, classifying their TF-DNA interactions as 'present', 'weak', or 'absent', with statistical significance for each classification.

Hum Mutat

October 2002

The human genome sequencing has spurred significant advancements in bioinformatics, particularly in analyzing single nucleotide polymorphisms (SNPs).
rSNP_Guide is a developed tool that predicts transcription factor binding sites based on DNA sequence alterations, which may relate to diseases.
The system has been validated using various genes linked to diseases and has shown effectiveness in analyzing important SNPs in both human and mouse genes.

Nucleic Acids Res

January 2002

SELEX_DB is an online resource that provides experimental data on in vitro selected DNA/RNA oligomers (aptamers) and tools for recognizing these sequences.
The new version includes a supplemental database, SYSTEM, which details the experimental design, and SELEX_TOOLS, an applet package for using this data in genomic annotation.
Cross-validation tests revealed that recognition accuracy improves with higher similarity between training and test sets of protein binding sequences, showing varying accuracy levels for natural sites, nearest homologs, and distant homologs.