
Cell Genomics, Journal Year: 2025, Volume and Issue: unknown, P. 100814 - 100814
Published: March 1, 2025
Language: Английский
Cell Genomics, Journal Year: 2025, Volume and Issue: unknown, P. 100814 - 100814
Published: March 1, 2025
Language: Английский
Science, Journal Year: 2023, Volume and Issue: 381(6664)
Published: Sept. 19, 2023
The vast majority of missense variants observed in the human genome are unknown clinical significance. We present AlphaMissense, an adaptation AlphaFold fine-tuned on and primate variant population frequency databases to predict pathogenicity. By combining structural context evolutionary conservation, our model achieves state-of-the-art results across a wide range genetic experimental benchmarks, all without explicitly training such data. average pathogenicity score genes is also predictive for their cell essentiality, capable identifying short essential that existing statistical approaches underpowered detect. As resource community, we provide database predictions possible single amino acid substitutions classify 89% as either likely benign or pathogenic.
Language: Английский
Citations
882Science, Journal Year: 2023, Volume and Issue: 379(6629)
Published: Jan. 19, 2023
The advent of clustered regularly interspaced short palindromic repeat (CRISPR) genome editing, coupled with advances in computing and imaging capabilities, has initiated a new era which genetic diseases individual disease susceptibilities are both predictable actionable. Likewise, genes responsible for plant traits can be identified altered quickly, transforming the pace agricultural research breeding. In this Review, we discuss current state CRISPR-mediated manipulation human cells, animals, plants along relevant successes challenges present roadmap future technology.
Language: Английский
Citations
617Nature Reviews Genetics, Journal Year: 2022, Volume and Issue: 24(3), P. 161 - 177
Published: Nov. 7, 2022
Language: Английский
Citations
324Nature reviews. Cancer, Journal Year: 2022, Volume and Issue: 22(5), P. 259 - 279
Published: Feb. 22, 2022
Language: Английский
Citations
296Nature Reviews Methods Primers, Journal Year: 2022, Volume and Issue: 2(1)
Published: Feb. 10, 2022
Language: Английский
Citations
207Molecular Cell, Journal Year: 2022, Volume and Issue: 82(2), P. 348 - 388
Published: Jan. 1, 2022
Language: Английский
Citations
156bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown
Published: Dec. 8, 2023
Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease designing novel that can address our most pressing challenges climate, agriculture and healthcare. Despite a surge machine learning-based protein models tackle these questions, an assessment their respective benefits challenging due use distinct, often contrived, experimental datasets, variable performance across different families. Addressing requires scale. To end we introduce ProteinGym, large-scale holistic set benchmarks specifically designed for fitness prediction design. It encompasses both broad collection over 250 standardized deep mutational scanning assays, spanning millions mutated sequences, as well curated clinical datasets providing high-quality expert annotations about mutation effects. We devise robust evaluation framework combines metrics design, factors known limitations underlying methods, covers zero-shot supervised settings. report diverse 70 high-performing various subfields (eg., alignment-based, inverse folding) into unified benchmark suite. open source corresponding codebase, MSAs, structures, model predictions develop user-friendly website facilitates data access analysis.
Language: Английский
Citations
96Nature Protocols, Journal Year: 2022, Volume and Issue: 17(11), P. 2431 - 2468
Published: Aug. 8, 2022
Language: Английский
Citations
81Cell, Journal Year: 2023, Volume and Issue: 186(10), P. 2256 - 2272.e23
Published: April 28, 2023
Language: Английский
Citations
57Nature Biotechnology, Journal Year: 2023, Volume and Issue: 41(10), P. 1446 - 1456
Published: Feb. 16, 2023
Most short sequences can be precisely written into a selected genomic target using prime editing; however, it remains unclear what factors govern insertion. We design library of 3,604 various lengths and measure the frequency their insertion four sites in three human cell lines, different editor systems varying DNA repair contexts. find that length, nucleotide composition secondary structure sequence all affect rates. also discover 3' flap nucleases TREX1 TREX2 suppress longer sequences. Combining features machine learning model, we predict relative insertions site with R = 0.70. Finally, demonstrate how our accurate prediction user-friendly software help choose codon variants common fusion tags insert at high efficiency, provide catalog empirically determined rates for over hundred useful
Language: Английский
Citations
50