Hi-C

Does a map-level insulation constraint improve sequence-based prediction of 3D genome folding? A Stage 1 Registered Report with a reverse-complement-equivariant state-space model (HiFold-Mamba)

The paper evaluates whether insulation-based losses improve sequence-based prediction of 3D genome folding using a reverse-complement-equivariant state-space model, finding improvements in boundary and loop prediction.

Evaluation of object detection neural networks to find topologically associated domains in bulk Hi-C data

This study evaluates YOLOv8 and Mask R-CNN for detecting TADs in bulk Hi-C data by converting Hi-C matrices into images and comparing their performance against reference TADs.

U-Chrom: a unified framework for single-cell and spatial 3D genome data

U-Chrom provides a unified framework for analyzing single-cell and spatial 3D genome data, showing consistent cell-type differences across assays.

Capture-(Hi)C analysis with PostChicago: Integrative metaprofiling and quantitative comparison of chromatin interactions

PostChicago provides a workflow for analyzing and comparing chromatin interactions from Capture-(Hi)C data, including quality control and visualization of metaprofiles.

Fetal signatures in the 3D genome of iPSC-derived neurons and their implications for disease modeling

This study compares chromatin architecture in iPSC-derived neurons to fetal and mature neurons, finding iPSC-derived neurons resemble fetal neurons and have distinct chromatin features.

Hi-cGAN: Prediction of Hi-C interaction matrices with conditional generative adversarial networks

Hi-cGAN predicts Hi-C interaction matrices using conditional generative adversarial networks, achieving better performance than existing methods at certain resolutions.

Integrative spatial profiling of 3D genome organization and gene expression in tissue

This paper introduces Spatial Hi-C-RNA, a spatial multi-omics technology that co-maps chromatin conformation and transcriptome in tissue, revealing spatially coherent domains and new insights into gene regulation.

Epigenetic Coalitions Couple Tissue Growth to Generate Periodic Colour Patterns in Birds

The paper shows how epigenetic coalitions in birds couple tissue growth to generate periodic color patterns through ASIP regulation and feedback loops.

BioMaster: Multi-agent System for Automated Bioinformatics Analysis Workflow

BioMaster automates complex bioinformatics workflows using a multi-agent system, improving accuracy, efficiency, and scalability across tasks like RNA-seq and Hi-C processing.

Systematic assessment of sequencing depth requirements for Hi-C-derived metrics

The paper assesses the sequencing depth requirements for Hi-C-derived metrics and finds that different metrics reach biologically meaningful accuracy at varying depths.

An Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain

The paper constructs an integrative single-cell epigenomic atlas of the adult mouse brain, mapping chromatin states and gene regulatory programs across 100 cell subclasses.

scWeave: A deep learning model that bidirectionally translates between gene expression and chromatin structure at single cell resolution

scWeave translates between gene expression and chromatin structure at single-cell resolution using deep learning, improving cross-modality inference across multiple datasets.

A generalizable Hi-C foundation model for chromatin architecture, single-cell and multi-omics analysis across species

HiCFoundation is a Hi-C-based model that integrates chromatin structure with epigenomic regulation across species, improving analysis of 3D genome architecture and single-cell data.

Generalisable tissue-wide molecular reconstruction from histology

GHIST+ reconstructs tissue-wide molecular maps from H&E histology, enabling cohort-scale molecular reconstruction from sparse spatial transcriptomic data.

Hyper3D-lite: count-preserving representation auditing for long-read multi-contact genome data

Hyper3D-lite audits long-read multi-contact genome data by preserving counts during all-pair projections to avoid overcounting contact evidence.

The HuBMAP Framework for Advancing Data FAIRness

The paper describes the HuBMAP framework for creating FAIR data through standardized metadata reporting across diverse assays and institutions.

From unsupervised clustering to atlas-guided annotation in cohort-scale spatial omics with HiCAT

HiCAT improves spatial omics annotation by combining unsupervised clustering with atlas guidance, revealing molecularly defined regions and enhancing downstream analysis.

ContextTAD: Context-aware boundary learning for TAD calling from Hi-C contact maps

ContextTAD improves TAD calling from Hi-C contact maps by learning context-aware boundary evidence, achieving strong performance across multiple evaluation settings.

BandHiC: a memory-efficient and user-friendly Python package for organizing and analyzing Hi-C matrices down to sub-kilobase resolution

BandHiC reduces memory usage for Hi-C matrices by 99% using a banded storage strategy while enabling efficient analysis of ultra-high-resolution data.

Agentic systems are adept at solving well-scoped, verifiable problems in computational biology

This paper introduces CompBioBench, a benchmark for evaluating agentic systems in computational biology, showing strong performance across diverse tasks.

Connecting multiway enhancer-promoter interactions to changes in gene expression in cancer

The paper develops an AMC model to link multiway enhancer-promoter contacts and enhancer activity to gene overexpression in prostate and breast cancer.

Evaluation of deep learning tools for chromatin contact prediction

This study benchmarks five deep learning models for predicting Hi-C contact maps, finding Epiphany performs best in accuracy, generalization, and loop detection.

Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC

TwinC predicts trans-chromosomal DNA contacts using DNA sequence and provides insights into their functional mechanisms.

Whole-genome 3D architectural screen reveals modulators of brain DNA structure

The paper introduces Plate-C, a high-throughput method for whole-genome 3D architecture profiling, and identifies modulators of DNA structure across multiple biological pathways and cell types.

Hi-C Calibration by Chemically Induced Chromosomal Interactions

This study uses a chemical method to create controlled chromosomal interactions in yeast to assess Hi-C's quantitative properties, finding it sensitive, unbiased, and linear.

Correcting Preprocessing Bias in Sparse Chromatin Contact Data Enables Physically Interpretable Reconstruction of Genome Architecture

The paper identifies preprocessing bias in chromatin contact data and introduces a framework to correct it, enabling physically interpretable genome architecture reconstruction.

SnakeHichipTF reveals transcription factor logic underlying enhancer-promoter wiring in the human brain

SnakeHichipTF decodes TF logic in enhancer-promoter wiring in human brain regions, revealing distinct regulatory programs and evolutionary elements.

Chiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping

Chiron3D predicts CTCF-mediated chromatin loops using a DNA-only model, revealing sequence determinants of loop strength and stability through interpretable deep learning.

ARCH3D: A foundation model for global genome architecture

This paper introduces ARCH3D, a foundation model for global genome architecture that captures spatial structure and interchromosomal interactions using a novel masked locus modeling task.

Modeling nascent transcription from chromatin landscape and structure

The paper introduces CLASTER, a deep learning model that predicts nascent transcription levels from chromatin landscape and 3D structure data, achieving high correlation with experimental measurements.