perturbation response prediction

A Three-View System for CRISPR-Cas12a crRNA Activity Ranking: When to Ensemble, When Context Matters More

The paper develops TriCasRank, a model for ranking CRISPR-Cas12a crRNA activity using sequence features, reference mapping, and historical data, showing improved correlation but comparable performance to an XGBoost model.

BioMeme: biological response memory for virtual cells

BioMeme predicts cell responses to new perturbations by recalling measured experiments, outperforming neural models in accuracy and speed.

Virtual dynamics of spatiotemporal single-cell interactions

CytoBridge reconstructs continuous virtual cell dynamics from sparse spatial transcriptomic data across development, regeneration, and neurodegeneration.

scDisentangle: sequential disentanglement for single-cell perturbation response prediction

scDisentangle predicts single-cell transcriptional responses to perturbations by decomposing expression into residual components, outperforming existing methods in cytokine stimulation, infection, and genetic perturbations.

Plate design confounds donor variation and model evaluation in single-cell perturbation screens

The paper shows that plate design confounds donor variation in single-cell perturbation screens and demonstrates how improved analysis methods can change interpretations of recent studies.

Spectral Adaptive Repositioning for Flow-Based Single-Cell Perturbation Modeling

SPEAR predicts cellular responses to perturbations by adaptively repositioning genes in a co-expression network using spectral encoding and generative modeling.

Where single-cell foundation models help: a benchmark of annotation, perturbation and regulatory inference against simple baselines

This paper benchmarks single-cell foundation models against baselines for annotation, perturbation and regulatory inference using diverse datasets.

PERTURBATION OF THE AMINO ACID STRESS RESPONSE PATHWAY EXPOSES A METABOLIC VULNERABILITY IN MULTIPLE AGGRESSIVE CANCER SUBTYPES

This study shows that disrupting the amino acid stress response pathway reduces tumor growth in multiple aggressive cancers by targeting chronic metabolic stress adaptation.

RELAY: Relational In-Context Learning for Cellular Perturbation Prediction

RELAY predicts cellular responses to perturbations by learning relational patterns from measured data, outperforming existing methods on unseen variable values and combinations.

Resolving how genetic perturbations act through gene regulatory paths

REGA-perturb resolves gene regulatory paths from genetic perturbations using reference epigenomes and RNA measurements, outperforming existing methods in identifying TF-target relationships and predicting regulatory changes.

Defining nutrient dependencies of intestinal Klebsiella pneumoniae guides rational probiotic engineering

This study identifies nutrient dependencies of intestinal Klebsiella pneumoniae and develops a probiotic consortium to restrict its expansion.

ExPert infers causal perturbations from cell states across biological and clinical contexts

ExPert infers causal perturbations from cell states by learning prototypes across 12 contexts, achieving high recall with low compute and validating findings in disease models.

De novo design of mini-proteins as specific binders to PACAP-38, a key mediator of migraine

This study designs mini-proteins that bind PACAP-38 with high affinity, showing improved potency and stability compared to earlier versions.

EMBER: Contextualized gene representations enable compositional prediction across cellular perturbations

EMBER, a gene-centric foundation model, improves cross-context perturbation-response prediction and genetic-interaction ranking using contextualized gene embeddings.

Single-cell perturbation prediction near experimental reproducibility with GENESIS

GENESIS predicts single-cell perturbation responses from experimental conditions, outperforming existing models and approaching experimental reproducibility.

DCAF: Unifying Data Validity, Evaluation Validity and Predictive Modeling for Single-cell Perturbation Simulation

DCAF improves single-cell perturbation simulation by addressing data, evaluation, and model validity, outperforming baselines in generalization and recapitulating regulatory heterogeneity in mouse brain.

Ultrasonic local anesthetic uncaging enables noninvasive, targeted, and transient knock-out of brain function

This paper demonstrates SonoRopi, a noninvasive method using ultrasound to transiently inhibit brain function in mice and rats.

Compact CRISPR-based genetic circuitry using a miniature genome-integrated Cas12m protein

A genome-integrated Cas12m in E. coli shows no measurable growth cost, reverses repression faster than dCas9, and supports NOT gates, a two-layer buffer and a two-pathway pigment circuit.

In Silico Design and Evaluation of CRISPR Cytosine Base Editing Strategy for Potential Correction of the ASPA Variant Associated with Canavan Disease

The paper designs and computationally evaluates a CRISPR base editing strategy to correct the ASPA variant associated with Canavan disease, identifying a candidate sgRNA with favorable editing characteristics and genome-wide specificity.

Characterization of the Preclinical in Vitro and in Vivo Pharmacokinetic Properties of the Cyclic Oligomeric Depsipeptide Ryanodine Receptor 2 Inhibitor ent-Verticilide

This study characterizes the pharmacokinetic properties of ent-verticilide, identifying limited intestinal availability and CYP-mediated metabolism as key factors affecting its oral exposure.

An improved CRISPR-LICHT screen of 120 Tdark genes illuminates new biologically relevant SOX2 targets in human brain organoids

The paper uses CRISPR-LICHT to screen SOX2 targets in human brain organoids, identifying 28 new genes involved in neural progenitor lineage expansion and survival.

How Much Can AI Virtual Cells Gain from Unified Perturbational Modeling?

This paper evaluates how unified perturbational modeling improves AI virtual cell predictors by integrating heterogeneous Perturb-seq datasets and achieving better performance across benchmarks.

Prediction transfer does not imply reliability transfer in single-cell foundation models

The paper investigates reliability transfer in single-cell foundation models across biological contexts and finds it varies independently from prediction transfer.

Centered cross-context perturbation transfer on the public 2025 Virtual Cell Challenge benchmark

The paper develops a method for cross-context perturbation transfer and differential-expression ranking, achieving competitive results on a benchmark challenge.

Averaging in gene perturbation benchmarks hides perturbation-strength variation: Consequences for model evaluation

The paper evaluates how averaging perturbation responses in gene perturbation benchmarks affects the ability to assess perturbation-strength variation, finding that current models fail to reliably recover perturbation identity.

Inference and validation of causal genetic interactions in aging human fibroblasts

This paper uses convergent cross mapping to infer causal genetic interactions from cross-sectional transcriptomic data of aging human fibroblasts and validates these interactions experimentally.

PETRO enables robust estimation of on-target perturbation effects in Perturb-seq

PETRO improves Perturb-seq analysis by reducing off-target bias and enabling robust target-level perturbation effect estimation.

Decision benchmarking reveals when protein foundation models add experimental value

This paper benchmarks decision strategies for protein engineering, showing when models and measurements improve decisions based on accumulated evidence.

Droplet-based organoid screens enable high-throughput identification of cancer vulnerabilities

This paper introduces a droplet-based organoid culture method for high-throughput screening of cancer vulnerabilities, identifying novel therapeutic targets in stomach cancer.

An Injectable Antisense Oligonucleotide (ASO) Approach to Treat Obesity in Preclinical Models

This paper demonstrates that injectable antisense oligonucleotides (ASO) can prevent and treat obesity in mice without significant loss of lean mass.