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Related papers: Variational auto-encoding of protein sequences

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Proteins are essential for life, and their structure determines their function. The protein secondary structure is formed by the folding of the protein primary structure, and the protein tertiary structure is formed by the bending and…

Biomolecules · Quantitative Biology 2024-03-11 Yanlin Zhou , Kai Tan , Xinyu Shen , Zheng He , Haotian Zheng

Spatially proximate amino acids in a protein tend to coevolve. A protein's three-dimensional (3D) structure hence leaves an echo of correlations in the evolutionary record. Reverse engineering 3D structures from such correlations is an open…

Quantitative Methods · Quantitative Biology 2013-01-15 Magnus Ekeberg , Cecilia Lövkvist , Yueheng Lan , Martin Weigt , Erik Aurell

A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sampling framework for evolving proteins in silico that…

Machine Learning · Computer Science 2023-04-10 Patrick Emami , Aidan Perreault , Jeffrey Law , David Biagioni , Peter C. St. John

Non protein coding regions of the human genome contain many complex patterns which regulate the cellular activity. Studying the human genome is limited by the lack of understanding of its features and their complex interactions. However,…

Genomics · Quantitative Biology 2017-08-15 Kerim Arioglu , Umut Eser

Variational auto-encoder frameworks have demonstrated success in reducing complex nonlinear dynamics in molecular simulation to a single non-linear embedding. In this work, we illustrate how this non-linear latent embedding can be used as a…

Machine Learning · Statistics 2018-01-03 Mohammad M. Sultan , Hannah K. Wayment-Steele , Vijay S. Pande

A method based on mapping a symbolic sequence into a set of patterns (strings resulting from the sequence parsing) is proposed as a tool for the reconstruction of ancestral sequences. The set union of patterns comprises all the patterns…

Genomics · Quantitative Biology 2015-04-16 Bohdan Kozarzewski

Autonomous driving presents a complex challenge, which is usually addressed with artificial intelligence models that are end-to-end or modular in nature. Within the landscape of modular approaches, a bio-inspired neural circuit policy model…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Anass Bairouk , Mirjana Maras , Simon Herlin , Alexander Amini , Marc Blanchon , Ramin Hasani , Patrick Chareyre , Daniela Rus

For the vast majority of naturally occurring, small, single domain proteins folding is often described as a two-state process that lacks detectable intermediates. This observation has often been rationalized on the basis of a nucleation…

Biomolecules · Quantitative Biology 2007-07-09 R. D. M. Travasso , P. F. N. Faisca , M. M. Telo da Gama

Several technological applications require the translation of a protein into a nucleic acid that codes for it (``backtranslation''). The degeneracy of the genetic code makes this translation ambiguous; moreover, not every translation is…

Biological Physics · Physics 2007-05-23 Andres Moreira

During their evolution, proteins explore sequence space via an interplay between random mutations and phenotypic selection. Here we build upon recent progress in reconstructing data-driven fitness landscapes for families of homologous…

Biomolecules · Quantitative Biology 2022-01-28 Matteo Bisardi , Juan Rodriguez-Rivas , Francesco Zamponi , Martin Weigt

Background: DNA, RNA, and protein sequence motifs can be recognition sites for biological functions such as regulation, DNA base modification, and molecular binding in general. The gain and loss of such motifs can carry important…

Genomics · Quantitative Biology 2022-10-19 Afif Elghraoui , Faramarz Valafar

Despite the large quantity of information available, thorough researches in various biological databases are still needed in order to reconstruct and understand the steps that lead to known or new phenomena. By using protein-protein…

Molecular Networks · Quantitative Biology 2014-12-03 Alberto Calderone

Cells regulate themselves via dizzyingly complex biochemical processes called signaling pathways. These are usually depicted as a network, where nodes represent proteins and edges indicate their influence on each other. In order to…

Molecular Networks · Quantitative Biology 2021-01-13 David Merrell , Anthony Gitter

We propose a single neural probabilistic model based on variational autoencoder that can be conditioned on an arbitrary subset of observed features and then sample the remaining features in "one shot". The features may be both real-valued…

Machine Learning · Statistics 2019-07-01 Oleg Ivanov , Michael Figurnov , Dmitry Vetrov

Protein folding is a problem of large interest since it concerns the mechanism by which the genetic information is translated into proteins with well defined three-dimensional (3D) structures and functions. Recently theoretical models have…

Biomolecules · Quantitative Biology 2007-05-23 Emidio Capriotti , Rita Casadio

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to…

Biological Physics · Physics 2017-08-18 Tsvi Tlusty , Albert Libchaber , Jean-Pierre Eckmann

Variant effect predictors (VEPs) aim to assess the functional impact of protein variants, traditionally relying on multiple sequence alignments (MSAs). This approach assumes that naturally occurring variants are fit, an assumption…

Machine Learning · Computer Science 2025-07-04 Antoine Honoré , Borja Rodríguez Gálvez , Yoomi Park , Yitian Zhou , Volker M. Lauschke , Ming Xiao

The evolutionary trajectory of a protein through sequence space is constrained by function and three-dimensional (3D) structure. Residues in spatial proximity tend to co-evolve, yet attempts to invert the evolutionary record to identify…

Biomolecules · Quantitative Biology 2015-03-13 Debora S. Marks , Lucy J. Colwell , Robert Sheridan , Thomas A. Hopf , Andrea Pagnani , Riccardo Zecchina , Chris Sander

The protein design problem involves finding polypeptide sequences folding into a given threedimensional structure. Its rigorous algorithmic solution is computationally demanding, involving a nested search in sequence and structure spaces.…

Quantum Physics · Physics 2024-07-11 Veronica Panizza , Philipp Hauke , Cristian Micheletti , Pietro Faccioli

Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. Moreover, when a large number of…

Quantitative Methods · Quantitative Biology 2011-01-18 Marta L. Gîrdea , Laurent Noé , Gregory Kucherov
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