Genetics

Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction

The decreasing cost of single-cell RNA sequencing (scRNA-seq) has enabled the collection of massive scRNA-seq datasets, which are now being used to train transformer-based cell foundation models (FMs). One of the most promising applications of these FMs is perturbation response modeling. This task aims to forecast how cells will respond to drugs or genetic interventions. Accurate perturbation resp...

Improvements to Casanovo, a deep learning de novo peptide sequencer

Casanovo is a state-of-the-art deep learning model for de novo peptide sequencing from mass spectrometry proteomics data. Here we report on a series of enhancements to Casanovo, aimed at improving the interpretability of the scores assigned to predicted peptides, generalizing the software for use in database search, speeding up training and prediction runtimes, and providing workflows and visualiz...

Hybrid Generative Model: Bridging Machine Learning and Biophysics to Expand RNA Functional Diversity

Functional RNAs perform diverse catalytic roles, yet natural sequences represent only a narrow subset of what is possible. Rediscovering such activiti...

Under which circumstances do genomic neural networks learn motifs and their interactions?

The use of neural networks to model genomic data in sequence-to-function scenarios has soared over the last decade. There remains much debate about wh...

GAME: Genomic API for Model Evaluation

The rapid expansion of genomics datasets and the application of machine learning has produced sequence-to-activity genomics models with ever-expanding...

Learned Geometry, Predicted Binding: Structurally-Based Prediction of Peptide:MHC Binding Using AlphaFold 3 Enables CD4 T Cell Epitope Prediction

The accurate prediction of T cell epitope peptides within proteins of interest has a wide range of applications, but is complicated by the multiple de...

Signatures of soft selective sweeps predominate in the yellow fever mosquito Aedes aegypti

The Aedes aegypti mosquito is a vector for human arboviruses and zoonotic diseases, such as yellow fever, dengue, Zika, and chikungunya, and as such p...

Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological...

The Fengshu Large Model for Wugu Fengdeng: An Innovation Engine for Knowledge Integration in the Soybean Field

Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emer...

Cell-free DNA fragmentomic characteristics in transposon elements inform molecular regulators and enhance cancer diagnosis

Fragmentomics of plasma cell-free DNA (cfDNA) are emerging diagnostic biomarkers in cancer liquid biopsy, while the molecular regulations of cfDNA fra...

RNA liquid biopsy via nanopore sequencing for novel biomarker discovery and cancer early detection

Liquid biopsies detect disease noninvasively by profiling cell-free nucleic acids that are secreted into the circulation. However, existing methods ex...

Recon8D: A metabolic regulome network from oct-omics and machine learning

To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ∼1000 different cancer cell lines ...

OmniPert: A Deep Learning Foundation Model for Predicting Responses to Genetic and Chemical Perturbations in Single Cancer Cells

In cancer, intra- and inter-patient heterogeneity presents a significant challenge for therapeutic management, as patients with apparently similar pro...

Temporal foundation model unveils ancient Hepatitis B virus evolution

Since ancient hepatitis B virus (HBV) sequencing data are scarce and incomplete, the evolutionary dynamics of HBV have long remained enigmatic. This d...

Machine Learning-Driven Optimization of Specific, Compact, and Efficient Base Editors via Single-Round Diversification

Cytosine and adenosine base editors show great potential in research and clinical applications. Current iterations of the deaminase—the enzyme used to...

AI Discovery of Mechanisms of Consciousness, Its Disorders, and Their Treatment

Understanding disorders of consciousness (DOC) remains one of the most challenging problems in neuroscience, hindered by the lack of experimental mode...

snATAC-Express infers Gene Expression from Prioritized Chromatin Accessibility Peaks using Machine Learning

Single cell multi-omic investigation opens-up new opportunities to understand mechanisms of gene regulation. Existing methods for inferring transcript...

spRefine Denoises and Imputes Spatial Transcriptomics with a Reference-Free Framework Powered by Genomic Language Model

The analysis of spatial transcriptomics is hindered by high noise levels and missing gene measurements, challenges that are further compounded by the ...

MORPH Predicts the Single-Cell Outcome of Genetic Perturbations Across Conditions and Data Modalities

Modeling cellular responses to genetic perturbations is a significant challenge in computational biology. Measuring all gene perturbations and their c...

Using spatial statistics to infer game-theoretic interactions in an agent-based model of cancer cells

Drug resistance in cancer is shaped not only by evolutionary processes but also by eco-evolutionary interactions between tumor subpopulations. These i...