Biology subjects

Liu, X.

Publications and source records attributed to Liu, X..

At least 253 records · Page 14Linked to original sources

bioRxiv2026

Estradiol modulates neuronal network hyperexcitability in select NDD risk genes

Sex hormone signaling during neurodevelopment may act as a modulator of risk for neurodevelopmental disorders (NDDs), including autism spectrum disorders (ASDs). By conducting a systematic and multi-modal evaluation of estradiol effects across loss-of-function deletions in 36 functionally diverse, large-effect ASD/NDD genes in human induced pluripotent stem cell-derived neurons and larval zebrafish, we uncover convergent and divergent gene-by-estradiol interactions at the transcriptomic, circuit, and behavioral levels. Whereas estradiol partially ameliorates dysregulated expression signatures across all ASD/NDD gene knockouts examined, it selectively and rapidly dampens network hyperexcitability phenotypes in only a subset of ASD/NDD gene knockouts. Two genes, ASH1L and SCN2A, are particularly responsive to estradiol treatment, with dramatic rescue of molecular and cellular effects in human knockout neurons, coupled with behavioral phenotypes in larval zebrafish mutants. The seven most estradiol responsive genes show enhanced protein-protein interaction network connectivity, strong co-expression in specific postnatal time periods, and enrichment in upper-layer mature excitatory neurons. Altogether, we describe distinct estradiol rescue in different modalities, elucidating shared transcriptomic effects as well as gene-specific cellular and behavioral rescue in the context of loss of function mutations of select ASD/NDD genes.

genomics↗

bioRxiv2026

Enhanced Hi-C Capture Analysis reveals complex regulatory architecture at the PICALM-EED locus for Alzheimer Disease

ObjectiveBoth the phosphatidylinositol binding clathrin assembly protein gene (PICALM) and the embryonic ectoderm development gene (EED) have been implicated as causal genes driving a genome-wide association for Alzheimer disease (AD) risk. We employed a new virtual approach using genome-wide chromatin interactions (Hi-C) called enhanced Hi-C Capture Analysis (eHiCA) to identify the genes and regulatory regions that are driving this important AD risk association. MethodsHi-C data from the frontal cortex of eight AD patients, as well as inducible pluripotent stem cell-derived microglia and spheroids of AD and control patients were used. We applied 14 eHiCA baits each containing a GWAS SNP to identify the cis regulatory interactions in this GWAS locus at a 5kb resolution. ResultsThe baits derived from the GWAS associated haplotype primarily interacted with the PICALM promoter and the large cis-regulatory elements cluster (CREe) lying upstream of the EED promoter. The EED promoter interacts with PICALM gene body and promoter region but not directly with the associated risk haplotype. Although the AD-associated variants segregate together as a haplotype in the population, each bait exhibited distinct functional chromatin interactions. InterpretationThe PICALM gene is the primary driver of the association in microglia along with the CREe locus. Different SNPs in a segregating haplotype can display different physical Hi-C interactions. This study demonstrates that eHiCA can help resolve the casual genes driving complex GWAS associations, opening new pathways to study Alzheimer disease and other disorders.

genomics↗

bioRxiv2026

Antibiotic Persistence Emerges from Cell-State-Driven Transcriptional Reprogramming

Antibiotic persistence allows a subpopulation of bacterial cells to survive antibiotic treatment without acquiring resistance mutations, often contributing to treatment failure. Although many genes have been linked to persistence, their deletion rarely abolishes the phenotype, highlighting redundancy in persistence mechanisms. Moreover, the transient and heterogeneous nature of persister formation has made it difficult to resolve its molecular basis using bulk analyses. Here, we use bacterial single-cell RNA sequencing and functional assays in Klebsiella pneumoniae to demonstrate how transcriptional heterogeneity and redundancy in stress responses shape persistence outcomes. Using growth phase as a biologically meaningful axis of transcriptional variation, we reveal that even within an isogenic population, distinct transcriptional responses can be induced and co-contribute to survival. These responses are shaped by the cells pre-treatment transcriptional state and the mechanism of antibiotic action. Genetic and environmental perturbations, such as rpoS deletion and nutrient supplementation, shift pre-treatment cell states and alter persistence frequencies. Our findings establish the biological significance of transcriptional heterogeneity shaped by pre-treatment cell states, providing a systems-level framework for understanding persistence and suggesting strategies to enhance antibiotic efficacy by modulating cell states.

microbiology↗

bioRxiv2026

Functional activation reveals a repressor-gated fourth type VI secretion system in clinical Pseudomonas aeruginosa

Pseudomonas aeruginosa is a major opportunistic pathogen in which the type VI secretion system (T6SS) contributes to interbacterial competition and virulence. While most strains encode three T6SSs, we here functionally characterize a fourth system (H4-T6SS) in a clinical P. aeruginosa isolate. The H4-T6SS gene cluster is transcriptionally silent under laboratory conditions. By promoter rewiring, we demonstrate that the H4-T6SS assembles a contractile machine and mediates effector secretion and robust inter- and intraspecific antagonism. We identify a dominant pore-forming effector and its secretion pathway and a silent yet conserved nuclease effector. Genetic and biochemical analyses show that H4-T6SS expression is activated by an H4-encoded transcriptional regulator and repressed by H-NS family proteins. Analysis of over 1,200 clinical isolates reveals that the H4-T6SS is distributed across lineages and geographic regions. Finally, we observe functional crosstalk between H4- and H2-T6SSs. Together, these findings establish H4-T6SS as a functional and repressor-gated secretion system that expands the competitive arsenal of clinical P. aeruginosa.

microbiology↗

bioRxiv2026

Lipid monounsaturation confers cold tolerance and improves tissue viability during hypothermic storage

The rapid loss of tissue viability during hypothermic storage frequently results in organ failure and high discard rates in transplantation. In contrast, ectothermic animals can tolerate prolonged exposure to low temperatures in their natural environments. Elucidating the mechanisms underlying this cold tolerance may therefore inform improved strategies for tissue preservation. Here, we investigate proteomic and metabolomic responses to cold exposure in the livers of two frog species from distinct habitats: the cold-sensitive African clawed frog (Xenopus laevis) and the cold-tolerant Northeastern Asian brown frog (Rana dybowskii). Cold exposure induced lipid mobilization in X. laevis, whereas it promoted phospholipid mono-unsaturation in R. dybowskii. Notably, treatment with monounsaturated fatty acids (MUFAs) or overexpression of stearoyl-CoA desaturase (SCD) reduced cell death during cold storage. Moreover, MUFA infusion significantly improved cell viability in mouse liver tissue under hypothermic conditions. Together, these findings suggest that lipid mono-unsaturation, an adaptive feature of cold-tolerant frogs, can be leveraged to enhance tissue preservation during cold storage.

biochemistry↗

bioRxiv2026

X-SPATIO: An Explanatory Deep Learning Pipeline for the Prediction and Visualization of Spatially Resolved Biomarker Expression in Triple-Negative Breast Cancer

Histopathologic evaluation remains central to cancer diagnosis and treatment planning, yet the molecular programs underlying distinct tissue morphologies are not routinely accessible in clinical workflows. Spatial transcriptomic/proteomic platforms provide region-specific molecular measurements but are limited by cost, throughput, and scalability. Most computational pathology models rely on either bulk tissue-based gene expression or a focused gene/protein expression-panel prediction, thereby obscuring subregion-specific morpho-molecular relationships and limiting spatial interpretation of a wider gene/protein expression network. This limitation is particularly significant in triple-negative breast cancer (TNBC), which exhibits pronounced spatial heterogeneity across tumor, stroma, and immune compartments. We developed X-SPATIO, a spatially compatible computational pipeline designed to directly link hematoxylin and eosin (H&E) morphology with region-matched mRNA and protein expression. The model was trained on H&E-defined regions of interest paired with spatially-resolved transcriptomic and proteomic data obtained from GeoMx Digital Spatial Profiler. Using a multiple-instance learning approach, X-SPATIO captures morpho-molecular associations, generating spatio-morphologic attention maps that indicate predictive tissue regions. X-SPATIO demonstrated strong performance across biologically relevant spatial biomarkers, achieving area under the curve values ranging [0.79, 0.97]. Attention maps revealed spatial patterns consistent with known biology, indicating alignment between learned features and tissue organization. By integrating spatial molecular ground truth with routine histopathology, X-SPATIO enables cost-effective inference of spatial biomarker expression and establishes a foundation for biologically grounded discovery and precision oncology in TNBC.

pathology↗

bioRxiv2026

Neural Activity Related Sodium (NARS) fMRI Resolves Millisecond Neuronal Dynamics in the Rodent Cortex

Brain-wide, noninvasive methods that directly resolve neuronal activity on millisecond timescales are still lacking in neuroimaging. Hemodynamic fMRI (1H-based) provides whole-brain maps of activity, yet its vascular origin creates spatial and temporal displacements from neuronal events that complicate interpretation, especially in disease conditions where neurovascular coupling is altered. Here, we developed an ultrafast 23Na fMRI platform at 14 T that combines a reshuffled k-t 3D gradient echo readout (TR/TE, 10ms/1ms) with an implantable RF coil and respiration-gated acquisition. This configuration provides the sampling rate and SNR needed to probe quadrupolar T2*-weighted single quantum sodium dynamics on the neuronal timescale. Across rats and mice, somatosensory forepaw stimulation produced a localized 23Na signal decrease of ~2-3% in the FP-S1, peaking ~10-30 ms post-stimulus. The activity pattern is well matched with conventional BOLD-fMRI maps acquired in the same animals. Trial-by-trial measurements during simultaneous iGluSnFR glutamate fiber photometry demonstrated that larger evoked glutamate transients coincided with larger NARS decreases, supporting a neuronal origin of the NARS contrast. We interpret the negative NARS response as a transient activity-dependent redistribution of sodium ions toward restricted, protein-rich microdomains, where more restricted rotational dynamics may accelerate T2*short decay and produce a 2-3% signal decrease without requiring large changes in bulk sodium concentration. Together, these results establish neural activity-related sodium (NARS) fMRI as a viable approach for direct, mesoscale neuronal mapping with MRI at millisecond resolution. Graphical AbstractA reshuffled k-t 3D gradient echo (GRE) readout with an implantable figure-8 RF coil and respiration-gated trials captures a ~2-3% negative 23Na response peaking 10-30 ms after forepaw stimulation in the FP-S1. NARS fMRI responses co-localize with BOLD-fMRI and scale with iGluSnFR glutamate transients, consistent with activity-dependent shifts toward short-T2* sodium microenvironments. Table of Contents (TOC) BlurbYu et al. introduce NARS-fMRI, an ultrafast 23Na method that resolves millisecond neuronal dynamics in rodent FP-S1. The negative sodium response (10-30 ms) co-localizes with BOLD and correlates with glutamate photometry, supporting a direct neuronal origin.

biophysics↗

bioRxiv2026

Structural Dynamics of the Dopamine D2 Receptor with a Non-Basic Ligand

Progress in understanding protein-ligand interactions is revolutionizing drug design, especially for G protein-coupled receptors (GPCRs), which are targets for 35% of marketed drugs.1 The dopamine D2 receptor (D2R) represents a key drug target in schizophrenia and Parkinsons disease.2 While structural studies have clarified its interactions with classical ligands, the behavior of atypical, non-basic ligands like D2AAK2 remains unclear. Notably, D2AAK2 shows strong selectivity for D2R over the closely related D3R, despite identical binding pocket composition. Here, we present a cryo-EM structure of D2AAK2 bound to D2R, showing that aspartate 3.32 serves as the main anchoring point, even though the compound lacks a basic nitrogen atom. Using enhanced sampling molecular dynamics simulations and experimental approaches, we uncover a complex binding energy landscape. Simulations suggest that D2AAK2 receptor subtype selectivity between identical binding sites arises from different energy barriers for their conformational changes. Non-basic ligands offer advantages such as better brain penetration and improved pharmacokinetics.3,4 This study provides the first structural insights into a non-basic ligand targeting D2R, paving the way for developing more effective, selective drugs.

pharmacology and toxicology↗

bioRxiv2026

Large-scale quantum computing framework enhances drug discovery in multiple stages

Coherent Ising machines (CIMs) excel at solving large-scale combinational optimization problems (COPs), but their insufficient long-term stability has hindered their applications in compute-intensive tasks like computer-aided drug discovery (CADD). By improving fiber vibration isolation and temperature control system, we have implemented a 2000-node CIM named QBoson-CPQC-3Gen achieving stable solutions over one hour on large-scale COPs. Graph-based encoding schemes were further introduced to realize a CIM-based CADD workflow including allosteric site detection, protein-peptide docking and intermolecular similarity calculation. CIM-based methods demonstrated superior speed and accuracy than heuristic algorithms. Especially, QBoson-CPQC-3Gen identified 2 novel druggable sites and bioactive compounds for 6 targets, which were further validated in vitro, in-cell and by crystal structures. Our contributions established a quantum-computing framework for multi-stage drug discovery, representing a significant advancement in both quantum computing applications and pharmaceutical research.

bioinformatics↗

bioRxiv2026

Ancient DNA reveals early use of melons in China's Song Dynasty

Melon (Cucumis melo L.) domestication is thought to have occurred independently once in Northeast Africa and twice in India, but archaeobotanical seed remains point to a possible additional domestication in China. Because Cucumis seeds are difficult to diagnose morphologically, genomic data from archaeological material are needed to evaluate these scenarios and reconstruct ancient melon traits. We sequenced two Song Dynasty melon seeds from Shuomen Gugang (China), recovering 4.6x and 1.7x nuclear genome coverage. Nuclear and chloroplast analyses place both seeds within cultivated C. melo from China, supporting introduction from the broader Asian domestication pool rather than independent Chinese domestication. To assess whether these seeds carried traits associated with sweet dessert melons, we examined loci underlying fruit phenotypes. Neither seed carried alleles for orange flesh; one harbored an allele linked to yellow/orange peel, the other possessed alleles associated with green flesh and reduced acidity. Since wild melons are monoecious, the presence of the derived andromonoecy allele in one seed, associated with rounder fruit shape, suggests early selection on fruit morphology. Together, these findings indicate that Song Dynasty melons were likely consumed as fresh or culinary fruits rather than as sweet dessert melons. Their flesh coloration resonates with Song-period aesthetic sensibilities, exemplified by jade-green celadon ceramics frequently crafted in melon-shaped forms. By anchoring East Asian archaeobotanical remains within modern melon genomic variation, this study provides a temporal framework for melon dispersal into China and shows how ancient genomics can illuminate past crop use.

evolutionary biology↗

bioRxiv2026

Salmonella exploits metal-responsive UMPylation to enable intracellular biphasic growth and antibiotic tolerance

Salmonella develops profound antibiotic tolerance during in vivo infection, directly contributing to antimicrobial treatment failure. Although phenotypic heterogeneity in bacterial growth rates underlies this tolerance, the exact mechanisms remain elusive. Here, we reveal that Salmonella exhibits a biphasic growth pattern within macrophages, with initial antibiotic levels modulating lag phase duration. Crucially, this growth plasticity is orchestrated by metal ion homeostasis and a reversible PTM-mediated protein phase transitions. Mechanistically, under stress conditions, enhanced Mn2+ uptake activates the UMPylator YdiU, which modifies critical translational machinery components such as elongation factor TufA. These modifications induce protein aggregation, leading to translational arrest and growth stasis. Conversely, upon stress alleviation, Salmonella accumulates Mg2+ and effluxes Mn2+, then the de-UMPylase YdiV is activated, which resolves protein aggregates to enable rapid bacterial resuscitation and proliferation. This metal-responsive proteostatic switch represents an evolutionarily conserved strategy for bacterial stress adaptation, with broad implications for combating antimicrobial tolerance. SIGNIFICANCE STATEMENTAntibiotic tolerance, a key cause of treatment failure in chronic infections, is often linked to bacterial phenotypic heterogeneity, yet the underlying regulatory mechanisms remain largely understood. This study uncovers a fundamental survival strategy employed by intracellular pathogen Salmonella, where host-derived manganese acts as a critical signal to induce a reversible, dormant state. We demonstrate that stress-induced Mn2+ influx activates widespread protein UMPylation, which functions as a molecular glue to drive the aggregation of essential proteins, thereby halting bacterial growth and conferring antibiotic tolerance. Crucially, this state is reversible upon stress relief through Mn2+ efflux and subsequent de-UMPylation, enabling rapid bacterial resuscitation. As an evolutionarily conserved mechanism of adaptive tolerance, this metal-ion-responsive switch, mediated by reversible protein UMPylation, identifies a key target for developing therapeutics against persistent bacterial infections.

microbiology↗

bioRxiv2026

Molecular basis of enfumafungin inhibition and resistance in Candida glabrata β-1,3-Glucan synthase FKS1

{beta}-1,3-Glucan synthase FKS1 is essential for fungal cell wall biogenesis and serves as a validated target of widely prescribed antifungal drugs. However, the molecular mechanism of pathogenic FKS1, its modes of inhibition, and the associated resistance mechanisms remain elusive, hindering the antifungal development. Here, we focus on Candida glabrata FKS1, a clinically relevant target frequently linked to antifungal resistance. We present cryo-EM structures of C. glabrata FKS1 in multiple detergent environments and in complex with the triterpenoid antifungal enfumafungin. Integrated functional studies revealed a key catalytic residue within the conserved ED motif and uncovered structural adaptations to different membrane-mimetic environments, rationalizing FKS1s sensitivity to its surrounding membrane context. Enfumafungin binds at the extracellular membrane leaflet of cgFKS1 transmembrane domain, engaging a convex surface separated from the cytosolic active site, consistent with its role as a non-competitive inhibitor. Further analyses identified key enfumafungin-binding residues from TM5-TM6 and elucidated the molecular basis of drug resistance in C. glabrata. Collectively, these findings establish a mechanistic framework for pathogenic FKS1 function and inhibition and provide a molecular basis for the rational design of next-generation antifungal therapeutics.

microbiology↗

bioRxiv2026

Identification and Characterization of Metastasis-initiating cells

Metastasis, the primary cause of cancer-related mortality, is a dynamic and complex process driven by a subset of cells known as metastasis-initiating cells (MICs). Accurate identification of MICs is therefore critical for metastasis diagnosis and therapeutic decision-making. However, current approaches rely either on mouse tracing experiments, which are difficult to translate to human systems, or on indirect strategies such as stemness, trajectory, pathway, and biomarker analyses that often yield inconsistent results. To address these limitations, we propose scMIC, a computational framework designed to explicitly and reliably identify MICs from single-cell data (available at https://github.com/swu13/scMIC). scMIC integrates an embedding-based representation, unbalanced optimal transport, and a top-k selection strategy to robustly capture metastasis-initiating potential. The framework was validated and applied across multiple cancer types, species, and multi-omics datasets. Our results demonstrate the reliability of scMIC for MIC identification, its potential clinical utility in metastasis prognosis, and its effectiveness in discovering metastasis-related gene programs and molecular biomarkers. Elucidating the mechanisms of metastasis initiation not only advances our understanding of metastatic progression but also enables the development of therapeutic strategies that target the more aggressive MIC population rather than non-MICs, thereby avoiding unintended increases in metastatic risk. Collectively, scMIC provides a powerful tool for cancer metastasis research and drug discovery.

bioinformatics↗

bioRxiv2026

Unravelling genome-wide mosaic microsatellite mutations at single-cell resolution

Short tandem repeats (STRs), or microsatellites, are highly mutable genomic elements that modulate gene regulations and are implicated in a range of human diseases. However, detecting mosaic STR mutations at single-cell resolution remains challenging due to both technical and biological complexities. To address this, we developed BayesMonSTR, a robust algorithm that enables accurate detection of mosaic STR mutations. Using this tool in single-cell analysis of human tissues, we reveal an accumulation of longer mosaic STR insertions and deletions (indels) in aging mitotic and post-mitotic cells. Strikingly, prefrontal cortex (PFC) neurons accumulate a higher burden of STR mutations than B cells or lung epithelium, with aged neurons exhibiting a particularly pronounced increase in longer STR deletions. These mutations are enriched at transcription start sites (TSSs) and active enhancers of highly expressed genes. Our work establishes a foundation for genome-wide, hypothesis-free discovery of disease-associated mosaic STR mutations and reveals a previously unexplored landscape of mosaic STR variation in development and aging.

bioinformatics↗

bioRxiv2026

The genetic repertoire of the deep sea: from sequence to structure and function

The deep sea as the largest and maybe most hostile environment on Earth is still underexplored especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures, and used it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity, yet substantial structural conservation of proteins. Especially proteins involved in replication, recombination, and repair were identified to be under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as a unique evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.

bioinformatics↗

bioRxiv2026

Integrative Multi-Omics Analysis Identifies a Functional Enhancer Driving Tumorigenesis in Head and Neck Squamous Cell Carcinoma

Enhancer is a critical epigenetic feature in head and neck squamous cell carcinoma (HNSCC), yet the functional roles of individual enhancers remain poorly understood. Here, we conducted an integrative multi-omics analysis based on publicly available ATAC-seq, H3K27ac ChIP-seq, transcriptomic profiling, and genetic association datasets to systematically map HNSCC-associated enhancers and their target genes. Integrating ATAC-seq and H3K27ac ChIP-seq, we identified 20,362 enhancers and 18,040 enhancer-associated genes, highlighting widespread regulatory complexity. Functional characterization of the TERT-associated enhancer GH05J001312 (GRCh38/hg38: chr5:1312099-1317743) revealed strong transcriptional activity in HNSCC. CRISPR-mediated deletion of a core sequence significantly reduced TERT expression, impaired cellular proliferation in vitro, and suppressed tumor growth in vivo, confirming its role as a key cis-regulatory element. RNA-seq analysis of enhancer-edited cells uncovered 742 differentially expressed genes enriched in cancer-related pathways, including MAPK and IL-17 signaling, indicating a broad transcriptional impact. Collectively, our findings establish GH05J001312 as a functional enhancer driving oncogenic programs in HNSCC and suggest enhancer-targeted strategies as a potential therapeutic avenue.

cancer biology↗

bioRxiv2026

MtDNA heteroplasmy controls tumor immune reprogramming through mitochondrial translation

Mitochondrial DNA (mtDNA) mutations are among the most frequent genetic alterations in human cancers, yet their molecular mechanisms in shaping tumor progression and metastasis under physiological conditions remain poorly understood. Here, we show that mtDNA heteroplasmy acts as a tumor cell-intrinsic rheostat that orchestrates fate decisions between progression and suppression. Moderate heteroplasmy induces a ribosomal storm of mitochondrial translation and ribosome biogenesis, driven by leucyl-tRNA synthetase 2 (LARS2). This response enhances metabolic fitness and licenses the secretion of S100A8/A9, enabling tumor cells to actively remodel the immune microenvironment through recruitment of myeloid-derived suppressor cells and exclusion of CD8 T cells, thereby promoting immune evasion and metastatic progression. In contrast, high heteroplasmy impairs tumorigenesis due to oxidative phosphorylation collapse. Disruption of LARS2, mitochondrial translation, or S100A9 signalling abrogates tumor progression. Our findings establish mtDNA heteroplasmy as a key regulator of cancer evolution, linking mitochondrial genetic variation to immune modulation, and reveal the LARS2-mitochondrial translation-S100A8/A9 axis as a therapeutically targetable programme within the pro-tumorigenic window of mtDNA heteroplasmy.

cancer biology↗

bioRxiv2026

An agentic framework turns patient-sourced records into a multimodal map of ALS heterogeneity

ALS progression is multidimensional, yet fragmented records and scalar outcomes obscure how patients move through disease states and how those states relate to molecular variation. MEDSTREM converts patient-held medical-record images into standardised longitudinal data, enabling bottom-up cohort construction. Using MEDSTREM-structured records from more than 8,000 AskHelpU participants together with PRO-ACT and Answer ALS, we developed DynaALS, the ALS Disease Dynamics Atlas. DynaALS represents ALS as a dynamic patient-state manifold that captures distinct directions of deterioration and patient movement between them over time. DynaALS retrieved population-referenced future states and decoded them into multidimensional clinical profiles without requiring patient-specific longitudinal histories. Motor-neuron RNA and chromatin profiles linked DynaALS states to developmental and regulatory programs, while neuromuscular-organoid single-cell multi-omics converged on a neural-developmental Netrin-DCC signalling axis across interacting cell types. By coupling MEDSTREM-enabled data construction to dynamic state modelling, DynaALS establishes a transferable patient-state engine for predictive and biologically interpretable disease models.

bioinformatics↗