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Ekaterina Khrameeva

dblp:62/11192 · also Ekaterina E. Khrameeva · DBLP profile ↗
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10ranked-venue papers
1as first author
3since 2021 · last 2025
0000-0001-6188-9139ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 8 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%
Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
epigenetics
0.912025
ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025
Bioinformatics and computational biology › epigenetics
epigenetic clock
0.912025
ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025
Information retrieval › evaluation
benchmark
0.912025
ComputAgeBench: Epigenetic Aging Clocks Benchmark · KDD (2) 2025
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.112012
Evidence for Widespread Association of Mammalian Splicing and Conserved Long-Range RNA Structures · RECOMB 2012
Bioinformatics and computational biology › RNA biology
RNA processing
0.112012
Evidence for Widespread Association of Mammalian Splicing and Conserved Long-Range RNA Structures · RECOMB 2012
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure analysis
0.112012
Evidence for Widespread Association of Mammalian Splicing and Conserved Long-Range RNA Structures · RECOMB 2012

Methods — techniques the papers use, named apart from their topics

DNA methylation profiling · 1.7
YearPublicationVenuePosition
2025 ComputAgeBench: Epigenetic Aging Clocks Benchmark
abstract
Age accelerating condition Healthy control p-value Age acceleration Blood data C h r o n o lo g ic a l A g e CpG site Dataset Averaging across cells ... ... ... ... ... CpG N CpG ...Figure 1: ComputAgeBench: the first comprehensive framework for benchmarking various epigenetic aging clock models.For a dataset 𝑋 , obtained by profiling DNA methylation at CpG sites in bulk blood samples, an aging clock model 𝑓 is trained to distinguish healthy individuals from those with pre-defined aging-accelerating conditions.
Dmitrii Kriukov, Evgeny Efimov, Ekaterina Kuzmina, Anastasiia Dudkovskaia, Ekaterina Khrameeva, Dmitry V. Dylov
KDD (2)5
2025 A hierarchical algorithm with randomized learning for robust tissue segmentation and classification in digital pathology
Svetlana Illarionova, Rifat Hamoudi, Margarita Zapevalina, Ilya Fedin, Nadezhda Alsahanova, Alexander V. Bernstein, Evgeny Burnaev, Vera Alferova, Ekaterina Khrameeva, Dmitrii G. Shadrin, Iman Talaat, Ahmed Bouridane, Maxim Sharaev
Inf. Sci.9
2023 HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biases
abstract
The chromatin interaction assays, particularly Hi-C, enable detailed studies of genome architecture in multiple organisms and model systems, resulting in a deeper understanding of gene expression regulation mechanisms mediated by epigenetics. However, the analysis and interpretation of Hi-C data remain challenging due to technical biases, limiting direct comparisons of datasets obtained in different experiments and laboratories. As a result, removing biases from Hi-C-generated chromatin contact matrices is a critical data analysis step. Our novel approach, HiConfidence, eliminates biases from the Hi-C data by weighing chromatin contacts according to their consistency between replicates so that low-quality replicates do not substantially influence the result. The algorithm is effective for the analysis of global changes in chromatin structures such as compartments and topologically associating domains. We apply the HiConfidence approach to several Hi-C datasets with significant technical biases, that could not be analyzed effectively using existing methods, and obtain meaningful biological conclusions. In particular, HiConfidence aids in the study of how changes in histone acetylation pattern affect chromatin organization in Drosophila melanogaster S2 cells. The method is freely available at GitHub: https://github.com/victorykobets/HiConfidence.
Victoria A Kobets, Sergey V. Ulianov, Aleksandra A. Galitsyna, Semen A. Doronin, Elena A. Mikhaleva, Mikhail S. Gelfand, Yuri Y. Shevelyov, Sergey V. Razin, Ekaterina Khrameeva
Briefings Bioinform.9
2018 Prediction of 3D Chromatin Structure Using Recurrent Neural Networks
Michal Rozenwald, Ekaterina Khrameeva, Grigory V. Sapunov, Mikhail S. Gelfand
BIBM2
2018 Prediction of chromatin spatial structure characteristics using machine learning methods
Sergei Starikov, Ekaterina Khrameeva, Mikhail S. Gelfand
BIBM2
2018 The chromatin structure of Dictyostelium discoideum
Olga Tsoy, Aleksandra A. Galitsyna, Ekaterina Khrameeva, Sergey V. Ulianov, Mikhail S. Gelfand, Sergey V. Razin
BIBM3
2018 Nuclear lamina maintains global spatial organization of chromatin in Drosophila cultured cells
Sergey V. Ulianov, Semen A. Doronin, Ekaterina Khrameeva, Pavel Kos, Sergey S. Starikov, Aleksandra A. Galitsyna, Artem Luzhin, Mikhail S. Gelfand, Alexander Chertovich, Sergey V. Razin, Yuri Y. Shevelyov
BIBM3
2018 Single-cell Hi-C demonstrates that TADs are stable units of Drosophila genome folding that persist in individual cells
Vlada S. Zakharova, Aleksandra A. Galitsyna, Kirill E. Polovnikov, Ekaterina Khrameeva, Mariya D. Logacheva, Elena A. Mikhaleva, Egor S. Vassetzky, Aleksey A. Gavrilov, Yuri Y. Shevelev, Sergey K. Nechaev, Sergey V. Ulianov, Sergey V. Razin
BIBM4
2012 Evidence for Widespread Association of Mammalian Splicing and Conserved Long-Range RNA Structures
Dmitri D. Pervouchine, Ekaterina Khrameeva, Marina Pichugina, Olexii Nikolaienko, Mikhail S. Gelfand, Petr Rubtsov, Andrey A. Mironov
RECOMB2
2012 Biases in read coverage demonstrated by interlaboratory and interplatform comparison of 117 mRNA and genome sequencing experiments
abstract
High-throughput sequencing of whole genomes and transcriptomes allows one to generate large amounts of sequence data very rapidly and at a low cost. The goal of most mRNA sequencing studies is to perform the comparison of the expression level between different samples. However, given a broad variety of modern sequencing protocols, platforms and versions thereof, it is not clear to what extent the obtained results are consistent across platforms and laboratories. The comparison of 117 human mRNA and genome high-throughput sequencing experiments performed on the Illumina and SOLiD platforms at 26 institutions all over the world demonstrated high dependency of the gene coverage profiles on the producing laboratory. Gene coverage profiles showed laboratory-specific non-uniformity that survived the 3'-bias correction and mappability normalization, suggesting that there are other yet unknown mRNA-associated biases.
Ekaterina Khrameeva, Mikhail S. Gelfand
BMC Bioinform.1