8 papers · ranked by Valyu relevance
Lee Organick, Siena Dumas Ang, Yuan-Jyue Chen, Randolph Lopez + 18 more
Current storage technologies can no longer keep pace with exponentially growing amounts of data. ^1^ Synthetic DNA offers an attractive alternative due to its potential information density of ~ 10^18^ B/mm^3^, 10^7^ times denser than magnetic tape, and potential durability of thousands of years.^2^ Recent advances in…
Louis Roberts, Juho Äijälä, Florian Burger, Cem Uran + 6 more
The cortex generates diverse neural dynamics, ranging from broadband fluctuations to narrowband oscillations in specific frequency bands. Here, we investigated whether broadband and oscillatory dynamics play different roles in the encoding and transmission of synergistic and redundant information. We used…
Parth K Raval, Wing Yui Ngan, Jenna Gallie, Deepa Agashe
The rate and accuracy of translation hinges upon multiple components – including transfer RNA (tRNA) pools, tRNA modifying enzymes, and rRNA molecules – many of which are redundant in terms of gene copy number or function. It has been hypothesized that the redundancy evolves under selection, driven by its impacts on…
Inbal Preuss, Michael Rosenberg, Zohar Yakhini, Leon Anavy
With the world generating digital data at an exponential rate, DNA has emerged as a promising archival medium. It offers a more efficient and long-lasting digital storage solution due to its durability, physical density, and high information capacity. Research in the field includes the development of encoding schemes…
Siobhan A. Cusack, Peipei Wang, Bethany M. Moore, Fanrui Meng + 4 more
Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene…
Tagir Akhmetshin, Arkadii Lin, Timur Madzhidov, Alexandre Varnek
Autoencoders represent a promising technique for the inverse quantitative structure-activity relationship (QSAR) task. However, undesirable bias, such as atom ordering, affects the neighbourhood behaviour of autoencoders’ latent space and, consequently, usage of the latent vectors as variables in machine-learning…
Oskar Weser, Björn Hein Hanke, Ricardo Mata
In this work, we present a fully automated method for the construction of chemically meaningful sets of non-redundant internal coordinates (also commonly denoted as Z-matrices) from the cartesian coordinates of a molecular system. Particular focus is placed on avoiding ill-definitions of angles and dihedrals due to…
Oskar Weser, Björn Hein Hanke, Ricardo Mata
In this work, we present a fully automated method for the construction of chemically meaningful sets of non-redundant internal coordinates (also commonly denoted as Z-matrices) from the cartesian coordinates of a molecular system. Particular focus is placed on avoiding ill-definitions of angles and dihedrals due to…