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Spatial 3D genome organization reveals intratumor heterogeneity in primary glioblastoma samples

Wang, Q., Wang, J., Mathur, R., Youngblood, M. W., Jin, Q., Hou, Y., Stasiak, L. A., Luan, Y., Zhao, H., Hilz, S., et al. (2025) · Science Advances · doi:10.1126/sciadv.adn2830 · Cited by 17 · see citing works

Deep learning exploration of single-cell and spatially resolved cancer transcriptomics to unravel tumour heterogeneity

Halawani, R., Büchert, M., & Chen, Y. P. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107274 · Cited by 16 · see citing works

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

Raffo, A., & Paulsen, J. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad302 · Cited by 15 · see citing works

Tracing cancer evolution and heterogeneity using Hi-C

Erdmann-Pham, D. D., Batra, S. S., Turkalo, T. K., Durbin, J., Blanchette, M., Yeh, I., Shain, A. H., Bastian, B. C., Song, Y. S., Rokhsar, D. S., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42651-2 · Cited by 16 · see citing works

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Breves, S. L., Giammartino, D. C. D., Nicholson, J., Cirigliano, S. M., Mahmood, S. R., Lee, U. J., Martinez‐Fundichely, A., Jungverdorben, J., Singhania, R., Rajkumar, S., et al. (2024) · Molecular Cell · doi:10.1016/j.molcel.2025.03.007 · Cited by 15 · see citing works

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes

Jiang, Z., Peng, Z., Wei, Z., Sun, J., Luo, Y., Bie, L., Zhang, G., & Wang, Y. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae789 · Cited by 14 · see citing works

Deciphering Hierarchical Chromatin Domains and Preference of Genomic Position Forming Boundaries in Single Mouse Embryonic Stem Cells

Ye, Y., Zhang, S., Gao, L., Zhu, Y., & Zhang, J. (2023) · Advanced Science · doi:10.1002/advs.202205162 · Cited by 12 · see citing works

HiCLift: a fast and efficient tool for converting chromatin interaction data between genome assemblies

Wang, X., & Yue, F. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad389 · Cited by 12 · see citing works

Characterization and integrated analysis of extrachromosomal DNA amplification in hematological malignancies

Zhang, H., Liu, B., Cheng, J., Li, Z., Jia, M.-F., Li, M., Zhao, L., Wang, L., & Xi, Y. (2024) · Neoplasia · doi:10.1016/j.neo.2024.101025 · Cited by 12 · see citing works

Decoding the fibromelanosis locus complex chromosomal rearrangement of black-bone chicken: genetic differentiation, selective sweeps and protein-coding changes in Kadaknath chicken

Shinde, S. S., Sharma, A., & Vijay, N. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1180658 · Cited by 11 · see citing works

Genome structure mapping with high-resolution 3D genomics and deep learningPreprint

Hong, C. K., Feng, F., Ramanathan, V., Liu, J., & Hansen, A. S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.06.650874 · Cited by 10 · see citing works

Emerging methods and applications in 3D genomics

Pedrotti, S., Castiglioni, I., Estrada, C. P., Zhao, L., Chen, J., Crosetto, N., & Bienko, M. (2024) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2024.102409 · Cited by 9 · see citing works

Comprehensive analysis of chromosome abnormalities by chromosome conformation based karyotyping (C-MoKa) in patients with conception failure and pregnancy loss

Bao, X., Yang, Y., Niu, W., Wang, Y., Shi, H. S., Zou, Y., Liu, Y., Wan, C., Ren, J., Lü, S., et al. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2024.120089 · Cited by 9 · see citing works

The 3D Genome Browser 2.0: an enhanced online platform for visualizing and analyzing 3D genome architecture

Yu, S., Fu, Y., Wong, J. H.-Y., Wang, J., Zhao, H., Zhao, J., & Yue, F. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1109 · Cited by 9 · see citing works

The promising role of nanopore sequencing in cancer diagnostics and treatment

Su, X., Lin, Q., Liu, B., Zhou, C., Lu, L., Lin, Z., Si, J., Ding, Y., & Duan, S. (2025) · Cell Insight · doi:10.1016/j.cellin.2025.100229 · Cited by 8 · see citing works

3D genome landscape of primary and metastatic colorectal carcinoma reveals the regulatory mechanism of tumorigenic and metastatic gene expression

Xu, X., Gan, J., Gao, Z., Li, R., Huang, D., Lin, L., Luo, Y., Yang, Q., Xu, J., Li, Y., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07647-2 · Cited by 8 · see citing works

Hi-C analysis of genomic contacts revealed karyotype abnormalities in chicken HD3 cell line

Maslova, A., Plotnikov, V., Nuriddinov, M., Gridina, M. M., Fishman, V., & Krasikova, A. (2023) · BMC Genomics · doi:10.1186/s12864-023-09158-y · Cited by 6 · see citing works

3C methods in cancer research: recent advances and future prospects

Yoon, I., Kim, U., Jung, K. O., Song, Y., Park, T., & Lee, D.-S. (2024) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01236-9 · Cited by 7 · see citing works

Chromosome conformation capture technologies as tools to detect structural variations and their repercussion in chromatin 3D configuration

Stephenson-Gussinye, A., & Furlan-Magaril, M. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1219968 · Cited by 7 · see citing works

Optical Genome Mapping Reveals the Landscape of Structural Variations and Their Clinical Significance in HBOC-Related Breast Cancer

Cheng, Y., Li, D., Bu, D., Han, L., Zhao, Y., Liu, J., Guo, X., Xu, H., & Yu, J. (2024) · Frontiers in Bioscience-Landmark · doi:10.31083/j.fbl2901002 · Cited by 6 · see citing works

Deciphering new insights into copy number variations as drivers of genomic diversity and adaptation in farm animal species

Celus, C. S., Ahmad, S. F., Gangwar, M., Kumar, S., & Kumar, A. (2024) · Gene · doi:10.1016/j.gene.2024.149159 · Cited by 5 · see citing works

Hi-C for genome-wide detection of enhancer-hijacking rearrangements in routine lymphoid cancer biopsies

Wu, J., Chu, A., Cho, J., Movahed-Ezazi, M., Galbraith, K., Fang, C. S., Yang, Y., Schroff, C., Sikkink, K. L., Perez-Arreola, M., et al. (2026) · Cell Genomics · doi:10.1016/j.xgen.2026.101166 · Cited by 4 · see citing works

Evaluation of Hi-C Sequencing for Detection of Gene Fusions in Hematologic and Solid Tumor Pediatric Cancer Samples

Schmitt, A. D., Sikkink, K. L., Ahmed, A. A., Melnyk, S., Reid, D., Meter, L. V., Guest, E. M., Lansdon, L. A., Pastinen, T., Pushel, I., et al. (2024) · Cancers · doi:10.3390/cancers16172936 · Cited by 4 · see citing works

Combining chromosome conformation capture and exome sequencing for simultaneous detection of structural and single-nucleotide variants

Gridina, M. M., Lagunov, T. A., Belokopytova, P. S., Torgunakov, N., Nuriddinov, M., Nurislamov, A. R., Назаренко, Л. П., Кашеварова, А. А., Лопаткина, М. Е., Vasilyev, S. А., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01471-3 · Cited by 4 · see citing works

AutoHiC: a deep-learning method for automatic and accurate chromosome-level genome assemblyPreprint

Jiang, Z., Peng, Z., Luo, Y., Bie, L., & Wang, Y. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.27.555031 · Cited by 4 · see citing works

Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single CellsPreprint

Chang, L., Xie, Y., Taylor, B., Wang, Z., Sun, J., Tan, T. M., Bejar, R. L., Chen, C. C., Furnari, F. B., Hu, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.18.590148 · Cited by 4 · see citing works

Evaluation of Hi-C sequencing for the detection of gene fusions in hematologic and solid pediatric cancer samplesPreprint

Schmitt, A. D., Sikkink, K. L., Ahmed, A. A., Melnyk, S., Reid, D., Meter, L. V., Guest, E. M., Lansdon, L. A., Pastinen, T., Pushel, I., et al. (2024) · medRxiv · doi:10.1101/2024.05.10.24306838 · Cited by 4 · see citing works

Systematic benchmarking of tools for structural variation detection using short- and long-read sequencing data in pigs

He, S., Song, B., Tang, Y., Qu, X., Li, X., Yang, X., Bao, Q., Fang, L., Jiang, J., Tang, Z., et al. (2025) · iScience · doi:10.1016/j.isci.2025.111983 · Cited by 3 · see citing works

The Bioinformatic Applications of Hi-C and Linked Reads

Jiang, L., Quail, M. A., Fraser-Govil, J., Wang, H., Shi, X., Oliver, K., Gómez, E., Yang, F., & Ning, Z. (2024) · Genomics Proteomics & Bioinformatics · doi:10.1093/gpbjnl/qzae048 · Cited by 3 · see citing works

Detection of Gene Fusions and Rearrangements in Formalin-Fixed, Paraffin-Embedded Solid Tumor Specimens Using High-Throughput Chromosome Conformation Capture

Galbraith, K., Wu, J., Sikkink, K. L., Mohamed, H., Reid, D., Perez-Arreola, M., Belton, J.-M., Nomikou, S., Melnyk, S., Yang, Y., et al. (2025) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2025.01.007 · Cited by 3 · see citing works

HYENA detects oncogenes activated by distal enhancers in cancer

Yu, A., Yesilkanal, A. E., Thakur, A., Wang, F., Yang, Y., Phillips, W., Wu, X., Muir, A., He, X., Spitz, F., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae646 · Cited by 2 · see citing works

A fast and adaptive detection framework for genome-wide chromatin loop mapping from Hi-C dataPreprint

Chen, S., Wang, J., Jung, I., Qiu, Z., Gao, X., & Li, Y. (2024) · Genome Research · doi:10.1101/gr.279274.124 · Cited by 3 · see citing works

Oncogenic drivers shape the tumor microenvironment in human gliomasPreprint

Zhao, B., Cho, C. Y., Ye, L., Keal, T., Mitchell, T., Martín-Barrio, I., Faraj, C. A., Unal, M., Alsing, J., Lawson, N. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.16.654515 · Cited by 3 · see citing works

Hi-C Technology Reveals Actionable Gene Fusions and Rearrangements in Diffuse Large B-Cell Lymphoma Unidentified by Conventional FISH

Liang, S., Ament, C., Klausner, M., Stinnett, V., Morsberger, L. A., Ghabrial, J., Middlezong, W., Schmitt, A. D., Hastie, A. R., & Zou, Y. S. (2025) · Genes · doi:10.3390/genes16091093 · Cited by 2 · see citing works

Strand-seq and the future of personalized genomics

Hanlon, V. C. T., & Lansdorp, P. (2026) · Nature Genetics · doi:10.1038/s41588-026-02548-4 · Cited by 1 · see citing works

SnapHiC-G: identifying long-range enhancer–promoter interactions from single-cell Hi-C data via a global background model

Liu, W., Zhong, W., Giusti‐Rodríguez, P., Jiang, Z., Wang, G. W., Sun, H., Hu, M., & Li, Y. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae426 · Cited by 3 · see citing works

Obtention of viable cell suspensions from breast cancer tumor biopsies for 3D chromatin conformation and single-cell transcriptome analysis

Stephenson-Gussinye, A., Rendón-Bautista, L. A., Ruiz-Medina, B. E., Olais, E. B., Pérez‐Molina, R., Marcial-Medina, C., Chávarri-Guerra, Y., Soto‐Pérez‐de‐Celis, E., Morales-Alfaro, A., Esquivel-López, A., et al. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2024.1420308 · Cited by 2 · see citing works

Charm is a flexible pipeline to simulate chromosomal rearrangements on Hi-C-like data

Nuriddinov, M., Belokopytova, P. S., & Fishman, V. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf081 · Cited by 2 · see citing works

Extreme structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programsPreprint

Xie, T., Danieli‐Mackay, A., Buccarelli, M., Barbieri, M., Papadionysiou, I., D’Alessandris, Q. G., Übelmesser, N., Vinchure, O. S., Lauretti, L., Fotia, G., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.20.537702 · Cited by 2 · see citing works

Haplotype-resolved de novo assembly revealed unique characteristics of alternative lengthening of telomeres in mouse embryonic stem cells

Lee, H., Niida, H., Sung, S.-H., & Lee, J. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae842 · Cited by 1 · see citing works

HiSVision: A Method for Detecting Large-Scale Structural Variations Based on Hi-C Data and Detection Transformer

Zhai, H., Dong, C., Wang, T., & Luo, J. (2024) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-024-00677-0 · Cited by 1 · see citing works

Chromatin hubs drive key regulatory networks in leukemia

Swaroop, A., & Yue, F. (2025) · Molecular Cell · doi:10.1016/j.molcel.2024.12.011 · Cited by 1 · see citing works

HiADN: Lightweight Resolution Enhancement of Hi-C Data Using High Information Attention Distillation Network

Li, P., Feng, J., Guo, J., & Liu, J. (2025) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbbio.2025.3614663 · Cited by 1 · see citing works

NFATC2::NUTM2 Fusion Defines a Novel Primary Pulmonary Epithelial Tumor With a Distinctive Immunophenotype

Feng, L., Liu, Q., Liu, X., Wang, S., Li, J., Han, Y., Mu, X., Wang, Y., Jiang, J., Wu, C., et al. (2026) · The American Journal of Surgical Pathology · doi:10.1097/pas.0000000000002533 · Cited by 1 · see citing works

Convergent evolution of complex structural variants drives therapy resistance in metastatic prostate cancer

Moreno-Rodriguez, T., ZHANG, M., Lundberg, A., Shrestha, R., Sjöström, M., Pasam, A., Chan, J., Devereux, L., Foye, A., Zhu, X., et al. (2026) · Genome biology · doi:10.1186/s13059-026-04074-2 · Cited by 1 · see citing works

[Advances in methods and applications of single-cell Hi-C data analysis].

Gong, H., Ma, F., & Zhang, X. (2023) · PubMed Central · doi:10.7507/1001-5515.202303046 · Cited by 1 · see citing works

Effectiveness of machine learning at modeling the relationship between Hi‐C data and copy number variation

Wang, Y., Sun, Y., Liu, Z., Chen, B., Chen, H., Ren, C., Lin, X., Hu, P., Jia, P., Xu, X., et al. (2024) · Quantitative Biology · doi:10.1002/qub2.52 · Cited by 2 · see citing works

Divergent 3D genome organization in livers of cave and surface morphs of Astyanax mexicanus as a potential driver of unique metabolic adaptations in cave environmentPreprint

Biswas, T., Li, H., & Rohner, N. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.30.615929 · Cited by 1 · see citing works

The 3D genome of pediatric B-cell precursor acute lymphoblastic leukemiaPreprint

Moura‐Castro, L. H., Aydın, E., Dushime, G. T., Woodward, E. L., Castor, A., Gunnarsson, R., Lilljebjörn, H., Olsson, L., Fioretos, T., Johansson, B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.22.666073 · Cited by 1 · see citing works

TASC: A transcriptome-driven machine learning classifier to explore molecular heterogeneity and relapse-associated programs in T-cell Acute Lymphoblastic LeukemiaPreprint

Benetti, C., Almolla, O., Gambi, G., Massa, A., Aifantis, I., Tsirigos, A., & Boccalatte, F. E. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.23.696007 · Cited by 1 · see citing works

Филостратиграфический анализ генов, ассоциированных с онкологическими заболеваниями человека

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-12

Роль гена MAKR6 в регуляции развития сосудистой системы в корне Arabidopsis thaliana L.

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-31

Нейросетевое моделирование изменения процессов клеточного дыхания под действием различных модуляторов в клеточных линиях цитоплазматических гибридов, несущих атеросклероз- ассоциированные мутации мтДНК

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-35

Влияние угольно-породовых твердых частиц ТЧ10 и ТЧ0,1, выделенных из проб снега, на частоту микроядер в культуре клеток А549

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-24

Gut microbiome stability: theoretical ecology and data driven approaches

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-48

Системная биология и биоинформатика (SBB-2023) : 14-я международная школа молодых ученых (22–26 мая 2023 г., Новосибирск, Россия) ; Тезисы докладов

(2023) · doi:10.18699/sbb-2023-00

Сравнительный анализ транскриптомов свободноживущей и паразитической стадий жизненного цикла некоторых групп нематод

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-07

Дифференциация островных и материковых популяций полевой мыши (Apodemus agrarius Pallas, 1771) юга Дальнего Востока России по шести микросателлитным локусам

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-29

Использование непараметрического бутстрепа для оценки популяционно-генетических параметров у организмов со смешанным типом размножения на основе микросателлитных данных

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-37

Анализ вариантов в генах адипоцитокинов методом таргетного секвенирования

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-02

Статистические и нейросетевые модели митофагии в цибридных клеточных линиях человека: роль атеросклероз- ассоциированных мутаций

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-03

Анализ регионов высокой гомозиготности в популяциях коренного населения Северной Евразии

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-15

Исследование термодинамических характеристик активированной кумаринами С-334 и С-525 хемилюминесценции под действием комплекса цитохрома С с кардиолипином

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-18

Новые маркерные гены резистентности опухолевых клеток к доксорубицину и разработка лекарственных кандидатов для ее терапии

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-23

Высокопроизводительная система анализа эффективности сплайсинга

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-21

Mapping of the Ant25 locus participating in proanthocyanidin synthesis in barley

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-50

Localization and numerical evaluation of myocardial fibrillation by mathematical image processing methods

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-40

A collection of genes for high protein and gluten content in grain introgressed into bread wheat from relative species: intra-chromosomal localization, molecular markers and agronomic effects

(2023) · doi:10.18699/sbb-2023-47

Разработка методов биоинформатического анализа эндосимбиотических бактерий

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-16

Кластерный анализ метаболомных профилей хрусталиков птиц как метод установления адаптивного ответа метаболома животных на внешнюю среду

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-11

Сравнительный анализ генетического разнообразия при половом и бесполом размножении в микросателлитных маркерах

(2023) · Systems Biology and Bioinformatics International Young Scientists School (SBB) · doi:10.18699/sbb-2023-28

EagleC Explorer: A desktop application for interactively detecting and visualizing SVs and enhancer hijacking on Hi-C contact mapsPreprint

Fu, Y., Wang, X., & Yue, F. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.07.552228 · Cited by 1 · see citing works

HiSVision: A Method for Detecting Large-Scale Structural Variations Based on Hi-C Data and Detection Transformer

Zhai, H., Dong, C., Wang, T., & Luo, J. (2024) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-024-00677-0 · Cited by 1 · see citing works

A method for structural variant detection using Hi-C contact matrix and neural networks

Shen, J., Wang, H., Zhai, H., Wang, J., & Luo, J. (2026) · Scientific Reports · doi:10.1038/s41598-026-37678-6

HiSV: A control-free method for structural variation detection from Hi-C data

Li, J., Gao, L., & Ye, Y. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010760 · Cited by 66 · see citing works

Analysis of Hi-C Data for Discovery of Structural Variations in Cancer

Song, F., Xu, J., Dixon, J. R., & Yue, F. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1390-0_7 · Cited by 23 · see citing works