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Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial intelligence-driven protein design. However, we lack a sufficient understanding of how…

Machine Learning · Computer Science 2022-06-29 Erik Nijkamp , Jeffrey Ruffolo , Eli N. Weinstein , Nikhil Naik , Ali Madani

Proteomics will celebrate its 20th year in 2014. In this relatively short period of time, it has invaded most areas of biology and its use will probably continue to spread in the future. These two decades have seen a considerable increase…

Genomics · Quantitative Biology 2014-03-24 Thierry Rabilloud , Pierre Lescuyer

The genetic code maps the sixty-four nucleotide triplets (codons) to twenty amino-acids. Some argue that the specific form of the code with its twenty amino-acids might be a 'frozen accident' because of the overwhelming effects of any…

Quantitative Methods · Quantitative Biology 2010-07-26 Tsvi Tlusty

We present the extention and application of a new unsupervised statistical learning technique--the Partition Decoupling Method--to gene expression data. Because it has the ability to reveal non-linear and non-convex geometries present in…

Quantitative Methods · Quantitative Biology 2015-09-24 Rosemary Braun , Gregory Leibon , Scott Pauls , Daniel Rockmore

Sequence coverage in MS analysis of protein digestion-derived peptides is a key issue for detailed characterization of proteins or identification at low quantities. In gel-based proteomics studies, the sequence coverage greatly depends on…

A generalized computational method for folding proteins with a fully transferable potential and geometrically realistic all-atom model is presented and tested on seven different helix bundle proteins. The protocol, which includes…

Biomolecules · Quantitative Biology 2009-11-11 Isaac A. Hubner , Eric J. Deeds , Eugene I. Shakhnovich

We review the recent progress in computational approaches to protein design which builds on advances in statistical-mechanical protein folding theory. In particular, we evaluate the degeneracy of the protein code (i.e. how many sequences…

Condensed Matter · Physics 2007-05-23 E. I. Shakhnovich

A Profile Mixture Model is a model of protein evolution, describing sequence data in which sites are assumed to follow many related substitution processes on a single evolutionary tree. The processes depend in part on different amino acid…

Populations and Evolution · Quantitative Biology 2020-07-07 Samaneh Yourdkhani , Elizabeth S. Allman , John A. Rhodes

This note represents the further progress in understanding the determination of the genetic code by Golden mean (Rakocevic, 1998). Three classes of amino acids that follow from this determination (the 7 "golden" amino acids, 7 of their…

Biomolecules · Quantitative Biology 2009-03-25 Miloje M. Rakocevic

Symbolic regression is the process of identifying mathematical expressions that fit observed output from a black-box process. It is a discrete optimization problem generally believed to be NP-hard. Prior approaches to solving the problem…

Neural and Evolutionary Computing · Computer Science 2021-11-19 T. Nathan Mundhenk , Mikel Landajuela , Ruben Glatt , Claudio P. Santiago , Daniel M. Faissol , Brenden K. Petersen

The advent of rapid and inexpensive DNA sequencing has led to an explosion of data waiting to be transformed into knowledge about genome organization and function. Gene prediction is customarily the starting point for genome analysis. This…

This methods paper presents computational protocols for the identification of non-coding RNA genes or RNA motifs within genomic sequences. An application to bacterial small RNA is proposed.

Quantitative Methods · Quantitative Biology 2015-12-23 Daniel Gautheret

Natural protein sequences somehow encode the structural forms that these molecules adopt. Recent developments in structure-prediction are agnostic to the mechanisms by which proteins fold and represent them as static objects. However, the…

Biomolecules · Quantitative Biology 2025-05-26 Ezequiel A. Galpern , Federico Caamaño , Diego U. Ferreiro

It has been repeatedly proposed to expand the scope for SETI, and one of the suggested alternatives to radio is the biological media. Genomic DNA is already used on Earth to store non-biological information. Though smaller in capacity, but…

Other Quantitative Biology · Quantitative Biology 2017-06-13 Vladimir I. shCherbak , Maxim A. Makukov

The role of positive selection in human evolution remains controversial. On the one hand, scans for positive selection have identified hundreds of candidate loci and the genome-wide patterns of polymorphism show signatures consistent with…

Populations and Evolution · Quantitative Biology 2013-08-23 David Enard , Philipp W. Messer , Dmitri Petrov

It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle these mutational profiles can be used to diagnose the tissue of origin, a critical task for the 3-5% of…

Methodology · Statistics 2020-07-14 Saptarshi Chakraborty , Colin B. Begg , Ronglai Shen

Computationally predicting protein-protein interactions (PPIs) is challenging due to the lack of integrated, multimodal protein representations. DPEB is a curated collection of 22,043 human proteins that integrates four embedding types:…

While accurate protein structure predictions are now available for nearly every observed protein sequence, predicted structures lack much of the functional context offered by experimental structure determination. We address this gap with…

Quantitative Methods · Quantitative Biology 2023-02-08 Nasim Abdollahi , Seyed Ali Madani Tonekaboni , Jay Huang , Bo Wang , Stephen MacKinnon

Protein folding and evolution are intimately linked phenomena. Here, we revisit the concept of exons as potential protein folding modules across 38 abundant and conserved protein families. Taking advantage of genomic exon-intron…

Biomolecules · Quantitative Biology 2024-01-05 Ezequiel A. Galpern , Hana Jaafari , Carlos Bueno , Peter G. Wolynes , Diego U. Ferreiro

DNA sequence encoding is fundamental to gene function prediction, protein synthesis, and diverse downstream biological tasks. Despite the substantial progress achieved by large-scale DNA sequence pretraining, existing studies have…

Machine Learning · Computer Science 2026-04-21 Zhijiang Tang , Jiaxin Qi , Yan Cui , Jinli Ou , Yuhua Zheng , Jianqiang Huang