Nicheformer: a foundation model for single-cell and spatial omics
New Results Nicheformer: a foundation model for single-cell and spatial omics View ORCID ProfileAnna C. Schaar, View ORCID ProfileAlejandro Tejada-Lapuerta, View ORCID ProfileGiovanni Palla, View ORCID ProfileRobert Gutgesell, View ORCID ProfileLennard Halle, View ORCID ProfileMariia Minaeva, View ORCID ProfileLarsen Vornholz, View ORCID ProfileLeander Dony, Francesca Drummer, View ORCID ProfileMo
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DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins
siRNADesign: A Graph Neural Network for siRNA Efficacy Prediction via Deep RNA Sequence Analysis
DeepRBP: A novel deep neural network for inferring splicing regulation
Generalized Biomolecular Modeling and Design with RoseTTAFold All-Atom
NuFold: A Novel Tertiary RNA Structure Prediction Method Using Deep Learning with Flexible Nucleobase Center Representation
CodonBERT: Large Language Models for mRNA design and optimization
Protein generation with evolutionary diffusion: sequence is all you need
Effect of Tokenization on Transformers for Biological Sequences
The human genome’s vocabulary as proposed by the DNA language model GROVER
Autoencoder-transformed transcriptome improves genotype-phenotype association studies
Distinguishing word identity and sequence context in DNA language models
RNAGEN: A generative adversarial network-based model to generate synthetic RNA sequences to target proteins
UNI-RNA: UNIVERSAL PRE-TRAINED MODELS REVOLUTIONIZE RNA RESEARCH
G2C4 targeting antisense oligonucleotides potently mitigate TDP-43 dysfunction in C9orf72 ALS/FTD human neurons
DNA language models are powerful zero-shot predictors of genome-wide variant effects
Multiple sequence-alignment-based RNA language model and its application to structural inference
A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
An in silico map of the SARS-CoV-2 RNA Structurome
The global population of SARS-CoV-2 is composed of six major subtypes