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Peptide nucleic acids (PNAs) are artificial nucleic acids with a peptide backbone instead of sugar phosphate backbone of DNA or RNA. Their resistance to degradation, selectivity and greater binding affinity in comparison to usual nucleic…

Biomolecules · Quantitative Biology 2019-10-18 Reyhane Alidousti , Mostafa Shakhsi-Niaee

Sorting cells based on their mechanical properties is essential for applications in disease diagnostics, cell therapy, and biomedical research. Deterministic Lateral Displacement (DLD) devices provide a label-free method for achieving such…

Quantitative Methods · Quantitative Biology 2025-12-08 Khayrul Islam , Mehedi Hasan , Yaling Liu

Deep learning (DL) is characterised by its dynamic nature, with new deep neural network (DNN) architectures and approaches emerging every few years, driving the field's advancement. At the same time, the ever-increasing use of mobile…

Machine Learning · Computer Science 2023-07-25 Ioannis Panopoulos , Sokratis Nikolaidis , Stylianos I. Venieris , Iakovos S. Venieris

In this paper, we introduce the first machine learning framework for predicting optimal processing times in Single-Level Tree Network (SLTN) architectures for the Divisible Load Theory (DLT) paradigm. Using a feedforward neural network(FNN)…

Machine Learning · Computer Science 2026-05-25 Bharadwaj Veeravalli

Diffusion generative models have emerged as a powerful framework for addressing problems in structural biology and structure-based drug design. These models operate directly on 3D molecular structures. Due to the unfavorable scaling of…

Biomolecules · Quantitative Biology 2024-05-10 Ian Dunn , David Ryan Koes

Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In order to assist with the diagnosis, computer-aided diagnosis…

Computer Vision and Pattern Recognition · Computer Science 2016-12-13 Stergios Christodoulidis , Marios Anthimopoulos , Lukas Ebner , Andreas Christe , Stavroula Mougiakakou

Nanovectors (NVs), based on nanostructured matter such as nanoparticles (NPs), have proven to perform as excellent drug delivery systems. However, due to the great variety of potential NVs, including NPs materials and their…

Neural and Evolutionary Computing · Computer Science 2021-12-06 Felipe J. Villaseñor-Cavazos , Daniel Torres-Valladares , Omar Lozano

Deep neural networks (DNN) have achieved unprecedented performance in computer-vision tasks almost ubiquitously in business, technology, and science. While substantial efforts are made to engineer highly accurate architectures and provide…

Image and Video Processing · Electrical Eng. & Systems 2022-09-08 Sumedha Singla

With the recent progress of information technology, the use of networked information systems has rapidly expanded. Electronic commerce and electronic payments between banks and companies, and online shopping and social networking services…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-02 Koichi Bando , Kenji Tanaka

Algorithms for machine learning-guided design, or design algorithms, use machine learning-based predictions to propose novel objects with desired property values. Given a new design task -- for example, to design novel proteins with high…

Machine Learning · Computer Science 2025-07-04 Clara Fannjiang , Ji Won Park

We use machine learning (ML) to infer stress and plastic flow rules using data from repre- sentative polycrystalline simulations. In particular, we use so-called deep (multilayer) neural networks (NN) to represent the two response…

Computational Physics · Physics 2018-09-05 Reese E. Jones , Jeremy A. Templeton , Clay M. Sanders , Jakob T. Ostien

With the advent of millimeter wave (mmWave) communications, the combination of a detailed 5G network simulator with an accurate antenna radiation model is required to analyze the realistic performance of complex cellular scenarios. However,…

Networking and Internet Architecture · Computer Science 2021-01-29 Mattia Lecci , Paolo Testolina , Mattia Rebato , Alberto Testolin , Michele Zorzi

Artificial neural networks have gone through a recent rise in popularity, achieving state-of-the-art results in various fields, including image classification, speech recognition, and automated control. Both the performance and…

Neural and Evolutionary Computing · Computer Science 2016-11-08 Sean C. Smithson , Guang Yang , Warren J. Gross , Brett H. Meyer

This chapter is a preprint from our book by , focusing on leveraging machine learning (ML) in chemical and polyolefin manufacturing optimization. It's crafted for both novices and seasoned professionals keen on the latest ML applications in…

Machine Learning · Computer Science 2024-01-23 Niket Sharma , Y. A. Liu

We introduce a multimodal deep learning framework, Prescriptive Neural Networks (PNNs), that combines ideas from optimization and machine learning, and is, to the best of our knowledge, the first prescriptive method to handle multimodal…

Machine Learning · Computer Science 2025-01-27 Dimitris Bertsimas , Lisa Everest , Vasiliki Stoumpou

Efficient and timely calculations of Machine Learning (ML) algorithms are essential for emerging technologies like autonomous driving, the Internet of Things (IoT), and edge computing. One of the primary ML algorithms used in such systems…

Hardware Architecture · Computer Science 2023-08-11 Christopher A. Metz

Machine learning (ML), especially deep learning is made possible by the availability of big data, enormous compute power and, often overlooked, development tools or frameworks. As the algorithms become mature and efficient, more and more ML…

Machine Learning · Computer Science 2018-06-21 Liangzhen Lai , Naveen Suda

When nanoparticles (NPs) are introduced into a biological solution, layers of biomolecules form on their surface, creating a corona. Understanding how the structure of the protein evolves into the corona is essential for evaluating the…

Deep learning (DL) techniques have had unprecedented success when applied to images, waveforms, and texts to cite a few. In general, when the sample size (N) is much greater than the number of features (d), DL outperforms previous machine…

Computer Vision and Pattern Recognition · Computer Science 2017-12-04 Thanh Hai Nguyen , Yann Chevaleyre , Edi Prifti , Nataliya Sokolovska , Jean-Daniel Zucker

Due to their inherent variabilities,nanomaterial-based sensors are challenging to translate into real-world applications,where reliability/reproducibility is key.Recently we showed Bayesian inference can be employed on engineered…

Applied Physics · Physics 2020-10-27 Davoud Hejazi , Shuangjun Liu , Amirreza Farnoosh , Sarah Ostadabbas , Swastik Kar