Natasha S. Latysheva

AlphaGenome Atlas: in silico mutagenesis of the entire human genome improves prioritization and interpretation of non-coding variants

Jun Cheng, Kyle R. Taylor, Lauren Nicolaisen, Joshua Pan et autres

A major challenge in genomics is deciphering the functional consequences of non-coding genetic variation. Here we present AlphaGenome Atlas, a comprehensive resource that enables the joint interpretation and prioritization of variant effects across the entire human genome. Using AlphaGenome, we predicted the …

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Advancing regulatory variant effect prediction with AlphaGenome

Natasha S. Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor et autres

Abstract Deep learning models that predict functional genomic measurements from DNA sequences are powerful tools for deciphering the genetic regulatory code. Existing methods involve a trade-off between input sequence length and prediction resolution, thereby limiting their modality scope and performance 1–5 . …

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AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model

Žiga Avsec, Natasha S. Latysheva, Jun Cheng, Guido Novati et autres

Deep learning models that predict functional genomic measurements from DNA sequence are powerful tools for deciphering the genetic regulatory code. Existing methods trade off between input sequence length and prediction resolution, thereby limiting their modality scope and performance. We present AlphaGenome, which …

us, gb (code pays fourni par la source)

Association of centenarian polygenic score with disability-free survival and its modification effects on aging outcomes

Takashi Sasaki, Shu Tadaka, Takumi Hirata, Yoshinori Nishimoto et autres

jp, us, gb, mx (code pays fourni par la source)

Genetic determinants of centenarian longevity, as quantified by the 'CentPGS' score, are associated with a lower risk of multiple age-related diseases and a longer healthspan.

Takashi Sasaki, Shu Tadaka, Takumi Hirata, Yoshinori Nishimoto et autres

jp, us, gb (code pays fourni par la source)

Molecular Signatures of Fusion Proteins in Cancer

Natasha S. Latysheva, M. Madan Babu

Although gene fusions are recognized as driver mutations in a wide variety of cancers, the general molecular mechanisms underlying oncogenic fusion proteins are insufficiently understood. Here, we employ large-scale data integration and machine learning and (1) identify three functionally distinct subgroups of …

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Pathway perturbations in signaling networks: Linking genotype to phenotype

Yongsheng Li, Daniel J. McGrail, Natasha S. Latysheva, S. Stephen Yi et autres

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Constraints and consequences of the emergence of amino acid repeats in eukaryotic proteins

Sreenivas Chavali, Pavithra L. Chavali, Guilhem Chalancon, Natalia Sánchez de Groot et autres

gb, be (code pays fourni par la source)

Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer

Natasha S. Latysheva, Matt E. Oates, Louis Maddox, Tilman Flock et autres

Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative …

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Discovering and understanding oncogenic gene fusions through data intensive computational approaches

Natasha S. Latysheva, M. Madan Babu

Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale …

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Cluster Analysis of p53 Binding Site Sequences Reveals Subsets with Different Functions

Ji‐Hyun Lim, Natasha S. Latysheva, Richard Iggo, Daniel Barker

p53 is an important regulator of cell cycle arrest, senescence, apoptosis and metabolism, and is frequently mutated in tumors. It functions as a tetramer, where each component dimer binds to a decameric DNA region known as a response element. We identify p53 …

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How do disordered regions achieve comparable functions to structured domains?

Natasha S. Latysheva, Tilman Flock, Robert J. Weatheritt, Sreenivas Chavali et autres

The traditional structure to function paradigm conceives of a protein's function as emerging from its structure. In recent years, it has been established that unstructured, intrinsically disordered regions (IDRs) in proteins are equally crucial elements for protein function, regulation and homeostasis. In …

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