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In spite of decades of research, much remains to be discovered about folding: the detailed structure of the initial (unfolded) state, vestigial folding instructions remaining only in the unfolded state, the interaction of the molecule with…

Biological Physics · Physics 2018-11-26 Walter A. Simmons

We design toy protein mimicking a machine-like function of an enzyme. Using an insight gained by the study of conformation space of compact lattice polymers, we demonstrate the possibility of a large scale conformational rearrangement which…

Soft Condensed Matter · Physics 2009-11-07 Alexander L. Borovinskiy , Alexander Yu. Grosberg

The polarizable embedding (PE) model is a fragment-based quantum-classical approach aimed at accurate inclusion of environment effects in quantum-mechanical response property calculations. The aim of this tutorial is to give insight into…

The spatial positioning of chromosomes relative to functional nuclear bodies is intertwined with genome functions such as transcription. However, the sequence patterns and epigenomic features that collectively influence chromatin spatial…

Genomics · Quantitative Biology 2023-07-04 Muyu Yang , Jian Ma

Introduction: While the origin and evolution of proteins remain mysterious, advances in evolutionary genomics and systems biology are facilitating the historical exploration of the structure, function and organization of proteins and…

Quantitative Methods · Quantitative Biology 2026-02-20 Gustavo Caetano-Anollés , M. Fayez Aziz , Fizza Mughal , Derek Caetano-Anollés

The torsional elasticity of semiflexible polymers like DNA is of biological significance. A mathematical treatment of this problem was begun by Fuller using the relation between link, twist and writhe, but progress has been hindered by the…

Soft Condensed Matter · Physics 2015-05-20 Joseph Samuel , Supurna Sinha

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

Branching architecture characterizes numerous systems, ranging from synthetic (hyper)branched polymers and biomolecules such as lignin, amylopectin, and nucleic acids to tracheal and neuronal networks. Its ubiquity reflects the many…

Soft Condensed Matter · Physics 2025-06-18 Domen Vaupotič , Jules Morand , Luca Tubiana , Anže Božič

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally-responsive materials therefore open up the possibility of creating a…

Many theoretical works have attempted to coarse grain gene expression at the level of transcription and translation via frameworks based on exclusion processes. Usually in these models the three-dimensional conformation of the substrates…

Statistical Mechanics · Physics 2019-05-22 Lucas D. Fernandes , Luca Ciandrini

Motivation: Site directed mutagenesis is widely used to understand the structure and function of biomolecules. Computational prediction of protein mutation impacts offers a fast, economical and potentially accurate alternative to laboratory…

Quantitative Methods · Quantitative Biology 2017-04-03 Zixuan Cang , Guo-Wei Wei

There is growing appreciation that gene function is connected to the dynamic structure of the chromosome. Here we explore the interplay between three-dimensional structure and transcriptional activity at the single cell level. We show that…

Molecular Networks · Quantitative Biology 2021-01-01 Lev Barinov , Sergey Ryabichko , William Bialek , Thomas Gregor

Transcriptomic data is a treasure-trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilised to…

Molecular Networks · Quantitative Biology 2023-12-13 Vikram Singh , Vikram Singh

Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature. We here present a community-driven initiative to address…

Eumelanin is regarded to be an attractive candidate material for biomedical applications. Despite many theoretical studies exploring the structure of eumelanin, an exact mapping of the energetic landscape of the very large phase space of…

Chemical Physics · Physics 2019-10-16 Oleg Sapunkov , Abhishek Khetan , Vikram Pande , Venkatasubramanian Viswanathan

Gene finding is the task of identifying the locations of coding sequences within the vast amount of genetic code contained in the genome. With an ever increasing quantity of raw genome sequences, gene finding is an important avenue towards…

Genomics · Quantitative Biology 2025-05-07 Frederikke I. Marin , Dennis Pultz , Wouter Boomsma

Short DNA linkers are increasingly being exploited for driving specific self-assembly of Brownian objects. DNA-functionalised colloids can assemble into ordered or amorphous materials with tailored morphology. Recently, the same approach…

Soft Condensed Matter · Physics 2015-01-12 Lucia Parolini , Bortolo M. Mognetti , Jurij Kotar , Erika Eiser , Pietro Cicuta , Lorenzo Di Michele

Natural organisms utilize distributed actuation through their musculoskeletal systems to adapt their gait for traversing diverse terrains or to morph their bodies for varied tasks. A longstanding challenge in robotics is to emulate this…

We introduce Tadpole, a novel foundation model for three-dimensional partial differential equations (PDEs) that addresses key challenges in transferability, scalability to high dimensionality, and multi-functionality. Tadpole is pre-trained…

Machine Learning · Computer Science 2026-05-18 Qiang Liu , Felix Koehler , Benjamin Holzschuh , Nils Thuerey

Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools.…

Biological Physics · Physics 2019-11-25 Frank Noé , Gianni De Fabritiis , Cecilia Clementi
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