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In sequential decision making, neural networks (NNs) are nowadays commonly used to represent and learn the agent's policy. This area of application has implied new software quality assessment challenges that traditional validation and…

Software Engineering · Computer Science 2023-12-18 Q. Mazouni , H. Spieker , A. Gotlieb , M. Acher

In the past decades, DNA has been intensely studied and exploited in different research areas of nanoscience and nanotechnology. At first glance, DNA-based nanophotonics seems to deviate quite far from the original goal of Nadrian Seeman,…

Biological Physics · Physics 2021-05-11 Na Liu

Composite DNA is a recent novel method to increase the information capacity of DNA-based data storage above the theoretical limit of 2 bits/symbol. In this method, every composite symbol does not store a single DNA nucleotide but a mixture…

Information Theory · Computer Science 2025-01-22 Tuan Thanh Nguyen , Chen Wang , Kui Cai , Yiwei Zhang , Zohar Yakhini

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient…

Biomolecules · Quantitative Biology 2019-05-13 Stefan Hammer , Christian Günzel , Mario Mörl , Sven Findeiß

One of the main goals of DNA nanotechnology is to provide a viable solution to the limitations of top-down approaches in microfabrication schemes. Although a completely practical bottom-up approach is yet to be realized, there has been…

Materials Science · Physics 2011-11-15 Junwye Lee , Sunho Kim , Junghoon Kim , Chang-Won Lee , Yonghan Roh , Sung Ha Park

DNA sequence analysis is fundamental to life science research. The rapid development of next generation sequencing (NGS) technologies, and the richness and diversity of applications it makes feasible, have created an enormous gulf between…

Computational Engineering, Finance, and Science · Computer Science 2013-10-29 Shel Swenson , Yogesh Simmhan , Viktor Prasanna , Manish Parashar , Jason Riedy , David Bader , Richard Vuduc

We describe a strategy for constructing codes for DNA-based information storage by serial composition of weighted finite-state transducers. The resulting state machines can integrate correction of substitution errors; synchronization by…

Information Theory · Computer Science 2016-11-18 Ian Holmes

Since the birth of computer and networks, fuelled by pervasive computing and ubiquitous connectivity, the amount of data stored and transmitted has exponentially grown through the years. Due to this demand, new solutions for storing data…

A novel computing model, called \emph{Probe Machine}, is proposed in this paper. Different from Turing Machine, Probe Machine is a fully-parallel computing model in the sense that it can simultaneously process multiple pairs of data, rather…

Computational Complexity · Computer Science 2016-03-01 Jin Xu

We live in a period where bio-informatics is rapidly expanding, a significant quantity of genomic data has been produced as a result of the advancement of high-throughput genome sequencing technology, raising concerns about the costs…

Quantitative Methods · Quantitative Biology 2023-03-10 Mehedi Hasan Sarkar , Adnan Ferdous Ashrafi

DNA labeling is a powerful tool in molecular biology and biotechnology that allows for the visualization, detection, and study of DNA at the molecular level. Under this paradigm, a DNA molecule is being labeled by specific k patterns and is…

Information Theory · Computer Science 2024-01-24 Dganit Hanania , Daniella Bar-Lev , Yevgeni Nogin , Yoav Shechtman , Eitan Yaakobi

Designing and generating new data under targeted properties has been attracting various critical applications such as molecule design, image editing and speech synthesis. Traditional hand-crafted approaches heavily rely on expertise…

Machine Learning · Computer Science 2024-03-19 Shiyu Wang , Yuanqi Du , Xiaojie Guo , Bo Pan , Zhaohui Qin , Liang Zhao

Differentiable programming is the combination of classical neural networks modules with algorithmic ones in an end-to-end differentiable model. These new models, that use automatic differentiation to calculate gradients, have new learning…

Dynamical Systems · Mathematics 2020-05-05 Adrián Hernández , José M. Amigó

Cells receive a wide variety of cellular and environmental signals, which must be processed combinatorially to generate specific and timely genetic responses. We present here a theoretical study on the combinatorial control and integration…

Soft Condensed Matter · Physics 2007-05-23 Nicolas E. Buchler , Ulrich Gerland , Terence Hwa

Nowadays, the rapid increases of the scale and complexity of the controlled plants bring new challenges such as computing power and storage for conventional control systems. Cloud computing is concerned as a powerful solution to handle the…

Systems and Control · Electrical Eng. & Systems 2023-03-06 Runze Gao , Yuanqing Xia , Li Dai , Zhongqi Sun

The deep Convolutional Neural Network (CNN) is the state-of-the-art solution for large-scale visual recognition. Following basic principles such as increasing the depth and constructing highway connections, researchers have manually…

Computer Vision and Pattern Recognition · Computer Science 2017-03-07 Lingxi Xie , Alan Yuille

Application-specific optical processors have been considered disruptive technologies for modern computing that can fundamentally accelerate the development of artificial intelligence (AI) by offering substantially improved computing…

Image and Video Processing · Electrical Eng. & Systems 2021-05-26 Tiankuang Zhou , Xing Lin , Jiamin Wu , Yitong Chen , Hao Xie , Yipeng Li , Jintao Fan , Huaqiang Wu , Lu Fang , Qionghai Dai

In computational molecular biology, gene regulatory binding sites prediction in whole genome remains a challenge for the researchers. Now a days, the genome wide regulatory binding site prediction tools required either direct pattern…

Genomics · Quantitative Biology 2010-02-06 Chandra Prakash Singh , Feroz Khan , Sanjay Kumar Singh , Durg Singh Chauhan

Discrete choice models are essential for modelling various decision-making processes in human behaviour. However, the specification of these models has depended heavily on domain knowledge from experts, and the fully automated but…

Machine Learning · Computer Science 2025-07-16 Fumiyasu Makinoshima , Tatsuya Mitomi , Fumiya Makihara , Eigo Segawa

As it is getting increasingly difficult to achieve gains in the density and power efficiency of microelectronic computing devices because of lithographic techniques reaching fundamental physical limits, new approaches are required to…

Emerging Technologies · Computer Science 2017-07-05 Jean C. Coulombe , Mark C. A. York , Julien Sylvestre
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