English
Related papers

Related papers: The Enhanced Double Digest Problem for DNA Physica…

200 papers

Graph neural networks (GNNs) are a powerful solution for various structure learning applications due to their strong representation capabilities for graph data. However, traditional GNNs, relying on message-passing mechanisms that gather…

Machine Learning · Computer Science 2024-03-19 Wei Duan , Jie Lu , Yu Guang Wang , Junyu Xuan

The DNA sequencing is the process of identifying the exact order of nucleotides within a given DNA molecule. The new portable and relatively inexpensive DNA sequencers, such as Oxford Nanopore MinION, have the potential to move DNA…

Computational Engineering, Finance, and Science · Computer Science 2019-01-09 Steven Y. Ko , Lauren Sassoubre , Jaroslaw Zola

Double-strand breaks (DSBs) in DNA are naturally occurring destructive events in all organisms that may lead to genome instability. Cells employ various repair methods known as non-homologous end joining (NHEJ), microhomology mediated end…

An old idea in optimization theory says that since the gradient is a dual vector it may not be subtracted from the weights without first being mapped to the primal space where the weights reside. We take this idea seriously in this paper…

Machine Learning · Computer Science 2024-12-09 Jeremy Bernstein , Laker Newhouse

As in many other scientific domains, we face a fundamental problem when using machine learning to identify proteins from mass spectrometry data: large ground truth datasets mapping inputs to correct outputs are extremely difficult to…

2D display is a fast and economical way of visualizing polymorphism and comparing genomes, which is based on the separation of DNA fragments in two steps, according first to their size and then to their sequence composition. In this paper,…

Biomolecules · Quantitative Biology 2009-10-29 Ana-Maria Florescu , Marc Joyeux , Benedicte Lafay

Packing problems are in general NP-hard, even for simple cases. Since now there are no highly efficient algorithms available for solving packing problems. The two-dimensional bin packing problem is about packing all given rectangular items,…

Neural and Evolutionary Computing · Computer Science 2020-07-28 Camelia-M. Pintea , Cristian Pascan , Mara Hajdu-Macelaru

As neural networks (NNs) are increasingly introduced into safety-critical domains, there is a growing need to formally verify NNs before deployment. In this work we focus on the formal verification problem of NN equivalence which aims to…

Machine Learning · Computer Science 2021-12-14 Samuel Teuber , Marko Kleine Büning , Philipp Kern , Carsten Sinz

Over the past two decades, a series of works have aimed at studying the problem of genome assembly: the process of reconstructing a genome from sequence reads. An early formulation of the genome assembly problem showed that genome…

Genomics · Quantitative Biology 2013-12-30 Henry Lin

Because of its high data density and longevity, DNA is emerging as a promising candidate for satisfying increasing data storage needs. Compared to conventional storage media, however, data stored in DNA is subject to a wider range of errors…

Information Theory · Computer Science 2020-08-20 Yuanyuan Tang , Farzad Farnoud

The existence of multiple load-solution mappings of non-convex AC-OPF problems poses a fundamental challenge to deep neural network (DNN) schemes. As the training dataset may contain a mixture of data points corresponding to different…

Machine Learning · Computer Science 2022-06-08 Xiang Pan , Wanjun Huang , Minghua Chen , Steven H. Low

A mechanism of double strand breaking (DSB) in DNA due to the action of two electrons is considered. These are the electrons produced in the vicinity of DNA molecules due to ionization of water molecules with a consecutive emission of two…

Biological Physics · Physics 2015-06-03 Eugene Surdutovich , Andrey V. Solov'yov

Inverse protein folding -- the task of predicting a protein sequence from its backbone atom coordinates -- has surfaced as an important problem in the "top down", de novo design of proteins. Contemporary approaches have cast this problem as…

Many researches demonstrated that the DNA methylation, which occurs in the context of a CpG, has strong correlation with diseases, including cancer. There is a strong interest in analyzing the DNA methylation data to find how to distinguish…

Genomics · Quantitative Biology 2020-01-29 Hong Yu , Zhanyu Ma

Predicting the secondary structure of RNA is a core challenge in computational biology, essential for understanding molecular function and designing novel therapeutics. The field has evolved from foundational but accuracy-limited…

Biomolecules · Quantitative Biology 2026-05-20 Giuseppe Sacco , Giovanni Bussi , Guido Sanguinetti

In DNA computing, it is impossible to decide whether a specific hybridization among complex DNA molecules is effective or not within acceptable time. In order to address this common problem, we introduce a new method based on the machine…

Quantitative Methods · Quantitative Biology 2018-07-03 Weijun Zhu

Longest Run Subsequence is a problem introduced recently in the context of the scaffolding phase of genome assembly (Schrinner et al., WABI 2020). The problem asks for a maximum length subsequence of a given string that contains at most one…

Data Structures and Algorithms · Computer Science 2021-06-23 Riccardo Dondi , Florian Sikora

DNA-mediated computing is a novel technology that seeks to capitalize on the enormous informational capacity of DNA and has tremendous computational ability to compete with the current silicon-mediated computing, due to massive parallelism…

Emerging Technologies · Computer Science 2017-09-01 Jian-Jun Shu , Qi-Wen Wang , Kian-Yan Yong

We consider the NP-hard Tree Containment problem that has important applications in phylogenetics. The problem asks if a given leaf-labeled network contains a subdivision of a given leaf-labeled tree. We develop a fast algorithm for the…

Computational Complexity · Computer Science 2017-02-22 Mathias Weller

Recently deep neural networks have been successfully applied in channel coding to improve the decoding performance. However, the state-of-the-art neural channel decoders cannot achieve high decoding performance and low complexity…

Machine Learning · Computer Science 2021-02-16 Siyu Liao , Chunhua Deng , Miao Yin , Bo Yuan