The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning.

Many genome-wide studies capture isolated moments in cell differentiation or organismal development. Conversely, longitudinal studies provide a more direct way to study these kinetic processes. Here, we present an approach for modeling gene-expression and chromatin kinetics from such studies: chronODE, an interpretable framework based on ordinary differential equations.

Recent advances and future prospects for blockchain in biomedicine.

Healthcare data are rapidly evolving with the introduction of new modalities and an exponential increase in volume. Current health data storage and communication services face major obstacles in terms of privacy, security, and operational efficiency in the face of this new data landscape. Blockchain technology, characterized by its immutability, auditability, and decentralization, is emerging as a promising solution.

Complex genetic variation in nearly complete human genomes.

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (median continuity of 130 Mb), closing 92% of all previous assembly gaps and reaching telomere-to-telomere status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8 and AMY1/AMY2, and fully resolve 1,852 complex structural variants.

An expanded reference catalog of translated open reading frames for biomedical research.

Non-canonical (i.e., unannotated) open reading frames (ncORFs) have until recently been omitted from reference genome annotations, despite evidence of their translation, limiting their incorporation into biomedical research.

A map of enhancer regions in primary human neural progenitor cells using capture STARR-seq.

Genome-wide association studies (GWASs) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. Here, we perform capture STARR-sequencing of over 70,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We select candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWASs.

Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD.

Post-traumatic stress disorder (PTSD) is a polygenic disorder occurring after extreme trauma exposure. Recent studies have begun to detail the molecular biology of PTSD. However, given the array of PTSD-perturbed molecular pathways identified so far, it is implausible that a single cell type is responsible.

College Community-Based Physical Activity Support at a Public University During the COVID-19 Pandemic: Retrospective Longitudinal Analysis of Intra- Versus Interpersonal Components for Uptake and Outcome Association.

Background: College students are vulnerable to setting long-term trajectories of low physical activity (PA) but are reachable via mobile health fitness tracking (eg, mobile health step counting) and interpersonal support tailored to the college community. However, no studies have statistically isolated the appeal and influence of these intra- and interpersonal components in college-based PA interventions.

Objective: This study retrospectively examined a college-based PA promotion program at a northeast US public university during the COVID-19 pandemic to (1) test the impact of student status on the use of intervention components and (2) determine whether such use was associated with successful retention and goal achievement in the program.

Spatially Resolved Panoramic in vivo CRISPR Screen via Perturb-DBiT.

Spatially resolved in vivo CRISPR screening integrates gene editing with spatial transcriptomics to examine how genetic perturbations alter gene expression within native tissue environments. However, current methods are limited to small perturbation panels and the detection of a narrow subset of protein-coding RNAs. We present Perturb-DBiT, a distinct and versatile approach for the simultaneous co-sequencing of spatial total RNA whole-transcriptome and single-guide RNAs (sgRNAs), base-by-base, on the same tissue section.

Scalable and efficient on-chain data management in blockchain for large biomedical data.

Blockchain technology is gaining traction in the biomedical sector due to its ability to improve trust and reduce the risk of fraud and errors in health data management. However, the large volume of biomedical datasets has slowed its adoption due to poor scalability. This challenge is especially relevant for applications that rely on blockchain's strong immutability by storing data directly on-chain.

A discard-and-restart MD algorithm for the sampling of protein intermediate states.

We introduce a discard-and-restart molecular dynamics (MD) algorithm tailored for the sampling of realistic protein intermediate states. It aids computational structure-based drug discovery by reducing the simulation times to compute a "quick sketch" of folding pathways by up to 2000×. The algorithm iteratively performs short MD simulations and measures their proximity to a target state via a collective variable loss, which can be defined in a flexible fashion, locally or globally.

Multi-omic Characterization of HIV Effects at Single Cell Level across Human Brain Regions.

HIV infection exerts profound and long-lasting neurodegenerative effects on the central nervous system (CNS) that can persist despite antiretroviral therapy (ART). Here, we used single-nucleus multiome sequencing to map the transcriptomic and epigenetic landscapes of postmortem human brains from 13 healthy individuals and 20 individuals with HIV who have a history of treatment with ART. Our study spanned three distinct regions-the prefrontal cortex, insular cortex, and ventral striatum-enabling a comprehensive exploration of region-specific and cross-regional perturbations.

A variational graph-partitioning approach to modeling protein liquid-liquid phase separation.

Graph neural networks (GNNs) have emerged as powerful tools for representation learning. Their efficacy depends on their having an optimal underlying graph. In many cases, the most relevant information comes from specific subgraphs.

Massively parallel reporter assay investigates shared genetic variants of eight psychiatric disorders.

A meta-genome-wide association study across eight psychiatric disorders has highlighted the genetic architecture of pleiotropy in major psychiatric disorders. However, mechanisms underlying pleiotropic effects of the associated variants remain to be explored. We conducted a massively parallel reporter assay to decode the regulatory logic of variants with pleiotropic and disorder-specific effects.

An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional Regulation.

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, The ENCODE consortium mapped biochemical signals across many cell types and tissues and integrated these data to develop a Registry of 0.9 million human and 300 thousand mouse candidate cis-Regulatory Elements (cCREs) annotated with potential functions.

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitations in that they measure heterogeneous behavior in a quantitative and unbiased fashion.

Network-based drug repurposing for psychiatric disorders using single-cell genomics.

Neuropsychiatric disorders lack effective treatments due to a limited understanding of underlying cellular and molecular mechanisms. To address this, we integrated population-scale single-cell genomics data and analyzed cell-type-level gene regulatory networks across schizophrenia, bipolar disorder, and autism (23 cell classes/subclasses). Our analysis revealed potential druggable transcription factors co-regulating known risk genes that converge into cell-type-specific co-regulated modules.

An integrative TAD catalog in lymphoblastoid cell lines discloses the functional impact of deletions and insertions in human genomes.

The human genome is packaged within a three-dimensional (3D) nucleus and organized into structural units known as compartments, topologically associating domains (TADs), and loops. TAD boundaries, separating adjacent TADs, have been found to be well conserved across mammalian species and more evolutionarily constrained than TADs themselves. Recent studies show that structural variants (SVs) can modify 3D genomes through the disruption of TADs, which play an essential role in insulating genes from outside regulatory elements' aberrant regulation.

Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.

The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between ligands and proteins. Many computational models for binding affinity prediction have been developed, but with varying results across targets.

The cell-type underpinnings of the human functional cortical connectome.

The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cerebral cortex. The cortical sheet can be broadly divided into distinct networks, which are embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here using microarray data from the Allen Human Brain Atlas and single-nucleus RNA-sequencing data from multiple cortical territories, we demonstrate that cell-type distributions are spatially coupled to the functional organization of cortex, as estimated through functional magnetic resonance imaging.

GENCODE 2025: reference gene annotation for human and mouse.

GENCODE produces comprehensive reference gene annotation for human and mouse. Entering its twentieth year, the project remains highly active as new technologies and methodologies allow us to catalog the genome at ever-increasing granularity. In particular, long-read transcriptome sequencing enables us to identify large numbers of missing transcripts and to substantially improve existing models, and our long non-coding RNA catalogs have undergone a dramatic expansion and reconfiguration as a result.

REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers.

Cryo-EM particle identification from micrographs ("picking") is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms ("pickers") identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers.

Binding profiles for 961 and transcription factors reveal tissue-specific regulatory relationships.

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms, (fly) and (worm). These data sets comprise 605 TFs identifying 3.