Effective gene expression prediction from sequence by integrating long-range interactions By using a new deep learning architecture, Enformer leverages long-range information to improve prediction of gene expression on the basis of DNA sequence. Žiga Avsec , Vikram Agarwal & David R. Kelley Res...
However, PERSIST can also operate in a supervised manner by incorporating cell-level annotations as the model’s prediction target, such as cell type labels or complementary epigenetic data like chromatin accessibility and methylation (Fig. 1A). As we show in our experiments, this gives PERSIST a...
Star4.3k A Cloud Native Batch System (Project under CNCF) kubernetesgolangmachine-learninggenehpcbigdatabatch-systems UpdatedDec 6, 2024 Go Gaius-Augustus/Augustus Star290 Genome annotation with AUGUSTUS geneannotationgenomediscoveryprediction UpdatedNov 25, 2024 ...
bioinformatics tools for gene function prediction ‐ in natural languages, difficulty for computers to processprotein structure comparison, detecting remote evolutionary relationships ‐ in absence of sequence similarityfunction prediction using integrated data ‐ interacting proteins, forming protein interaction ...
BRAKER2 is an extension of BRAKER1 which allows forfully automated trainingof the gene prediction tools GeneMark-EXR14,R15,R17,F1and AUGUSTUS from RNA-Seq and/or protein homology information, and that integrates the extrinsic evidence from RNA-Seq and protein homology information into theprediction...
Table S4. GO term enrichment analysis for gene trends, related to Figure 2 Table S5. Inferred CREs, GO term enrichments, and TF enrichments, related to Figure 5 Table S6. Disease age prediction and analysis of PNs predicted to reach postnatal maturity in organoids, related to Figure 7Volum...
Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a mann
The performance of the method was not affected by the removal of paralogous genes from the clusters (Figure 9B), and clustering of such genes is clearly not a significant source of false positive motif prediction. Consequently, we decided to include the paralogs in the final analysis since we...
This prediction accuracy substantially increases the utility of polygenic scores as tools in research. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription ...
Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction Corey Weistuch Kevin A. Murgas Joseph O. Deasy ResearchOpen Access08 Nov 2024Scientific Reports Volume: 14, P: 27230 TET2 germline variants promote kidney disease by impairing DNA repair and activating cytosolic nucleoti...