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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

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Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

Response to Comment on (Novel two-dimensional porous graphitic carbon nitride C6N7 monolayer: A First-principle calculations [Appl. Phys. Lett. 2021, 119, 142102])

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arXiv 2022年

作者： Bafekry, Asadollah Faraji, Mehrdad Fadlallah, Mohamed M. Sarsari, I. Abdolhosseini Jappor, Hamad R. Fazeli, Sara Ghergherehchi, Mitra Department of Radiation Application Shahid Beheshti University Tehran Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Material Science and Engineering Sharif University of Technology PO Box 11155-9466 Tehran Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Recently, reported a comments on the our paper [Appl. Phys. Lett. 119, 142102(2021)]. With our response, the APL journal rejected their non scientificcomments. There are some ambiguities about their claim: 1-They can check thephonon dispersion of their structure to see ZA out-of-plane mode. 2-They reportthe uniaxial stress-strain responses in Fig 2., which is unrelated to ourpaper. For a more helpful understanding of the mechanical properties of thenovel C6N7 monolayer, they can publish a paper. 3-They mentioned: Using the DFTmethod and with assuming a thickness of 3.35 A for the C6N7 monolayer based ongraphene thickness. Why did they choose this thickness while we know our C6N7monolayer is at without buckling? The distance of ZA out-of-plane movement ofions in C6N7 is different from Graphene. © 2022, CC BY.

关键词： Monolayers

Biopsy-free Virtual Histology of Skin Using Reflectance Confocal Microscopy and Deep Learning

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Biopsy-free Virtual Histology of Skin Using Reflectance Conf...

Conference on Lasers and Electro-Optics (CLEO)

作者： Jingxi Li Jason Garfinkel Xiaoran Zhang Di Wu Yijie Zhang Kevin de Haan Hongda Wang Tairan Liu Bijie Bai Yair Rivenson Gennady Rubinstein Philip O. Scumpia Aydogan Ozcan Electrical and Computer Engineering Department University of California Los Angeles CA USA Bioengineering Department University of California Los Angeles CA USA California NanoSystems Institute (CNSI) University of California Los Angeles CA USA Dermatology and Laser Centre Studio City CA USA Computer Science Department University of California Los Angeles CA USA Division of Dermatology University of California Los Angeles CA USA Department of Dermatology Veterans Affairs Greater Los Angeles Healthcare System Los Angeles CA USA Department of Surgery University of California Los Angeles CA USA

We report in vivo virtual histology of skin without a biopsy, where deep learning is used to virtually stain tissue and generate hematoxylin and eosin (H&E)-like microscopic images of skin using a reflectance conf... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Reflectivity Deep learning In vivo Histopathology Microscopy Biopsy Lasers and electrooptics

A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

Preemptive periodic epidemic control reduces life and healthcare system costs without aggravation of social and economic losses

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arXiv 2021年

作者： De Nicolao, Giuseppe Colaneri, Marta Filippo, Alessandro Di Blanchini, Franco Bolzern, Paolo Colaneri, Patrizio Giordano, Giulia Bruno, Raffaele Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Division of Infectious Diseases I Fondazione IRCCS Policlinico San Matteo Pavia Italy Department of Mathematics Computer Science and Physics University of Udine Udine Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy Department of Industrial Engineering University of Trento Trento Italy Department of Clinical Surgical Diagnostic and Pediatric Sciences University of Pavia Pavia Italy

Many countries are managing COVID-19 epidemic by switching between lighter and heavier restrictions. While an open-close and a close-open cycle have comparable socio-economic costs, the former leads to a much heavier burden in terms of deaths and pressure on the healthcare system. An empirical demonstration of the toll ensuing from procrastination was recently observed in Israel, where both cycles were enforced from late August to mid-December 2020, yielding some 1,600 deaths with open-close compared to 440 with close-open. © 2021, CC BY.

关键词： Losses

Magnetically tuned continuous transition from weak to strong coupling in terahertz magnon polaritons

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Physical Review Research 2023年第1期5卷 L012039-L012039页

作者： Andrey Baydin Kenji Hayashida Takuma Makihara Fuyang Tay Xiaoxuan Ma Wei Ren Guohong Ma G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Shixun Cao Motoaki Bamba Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Division of Applied Physics Graduate School of Engineering Hokkaido University Sapporo Hokkaido 060-8628 Japan Department of Physics and Astronomy Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics International Center of Quantum and Molecular Structures and Materials Genome Institute Shanghai University 200444 Shanghai China Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan The Hakubi Center for Advanced Research Kyoto University Kyoto 606-8502 Japan Department of Physics I Kyoto University Kyoto 606-8502 Japan PRESTO Japan Science and Technology Agency Kawaguchi 332-0012 Japan Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling transition as a function of magnetic field. We observed a Rabi splitting of a terahertz magnon mode in yttrium orthoferrite above a threshold magnetic field of ∼14 T. Based on a microscopic theoretical model, we show that with increasing magnetic field the magnons transition into magnon polaritons through an exceptional point, which will open up new opportunities for in situ control of non-Hermitian systems.

关键词： Antiferromagnetism High magnetic fields Magneto-optics Magnons Polaritons Non-Hermitean systems Terahertz time-domain spectroscopy Transfer matrix method

Electromagnetic-polarization selective composites with quasi-1D van der Waals metallic fillers

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arXiv 2021年

作者： Barani, Zahra Kargar, Fariborz Ghafouri, Yassamin Baraghani, Saba Sudhindra, Sriharsha Mohammadzadeh, Amirmahdi Salguero, Tina T. Balandin, Alexander A. Center Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Department of Chemical and Environmental Engineering University of California RiversideCA92521 United States Department of Chemistry University of Georgia AthensGA30602 United States Material Science and Engineering Program University of California RiversideCA92521 United States

We report on the preparation of flexible polymer composite films with aligned metallic fillers comprised of atomic chain bundles of the quasi-one-dimensional (1D) van der Waals material tantalum triselenide, TaSe3. The material functionality, embedded at the nanoscale level, is achieved by mimicking the design of an electromagnetic aperture grid antenna. The processed composites employ chemically exfoliated TaSe3 nanowires as the grid building blocks incorporated within the thin film. Filler alignment is achieved using the "blade coating" method. Measurements conducted in the X-band frequency range demonstrate that the electromagnetic transmission through such films can be varied significantly by changing the relative orientations of the quasi-1D fillers and the polarization of the electromagnetic wave. We argue that such polarization-sensitive polymer films with quasi-1D fillers are applicable to advanced electromagnetic interference shielding in future communication systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Van der Waals forces

Untrained, Physics-Informed Neural Networks for Structured Illumination Microscopy

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arXiv 2022年

作者： Burns, Zachary Liu, Zhaowei Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Material Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Center for Memory and Recording Research University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States

In recent years there has been great interest in using deep neural networks (DNN) for super-resolution image reconstruction including for structured illumination microscopy (SIM). While these methods have shown very promising results, they all rely on data-driven, supervised training strategies that need a large number of ground truth images, which is experimentally difficult to realize. Additionally, such trained methods are prone to overfitting and often fail to generalize well to data that is out of the training distribution making them unsuitable as tools of discovery. For SIM imaging, there exists a need for a flexible, general, and open-source reconstruction method that can be readily adapted to different forms of structured illumination. We demonstrate that we can combine a deep neural network with the forward model of the structured illumination process to reconstruct sub-diffraction images without training data. The resulting physics-informed neural network (PINN) can be optimized on a single set of diffraction limited sub-images and thus doesn’t require any training set. We show with simulated and experimental data that this PINN can be applied to a wide variety of SIM methods by simply changing the known illumination patterns used in the loss function and can achieve resolution improvements that match well with theoretical expectations. © 2022, CC BY.

关键词： Deep neural networks

Architecture and implementation of ulrb algorithm in R

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Ecological Informatics 2025年 90卷

作者： Pascoal, Francisco Costa, Rodrigo Torgo, Luís Magalhães, Catarina Branco, Paula Departamento de Biologia Faculdade de Ciências Universidade do Porto Portugal Centro Interdisciplinar de Investigação Marinha e Ambiental Universidade do Porto Porto Portugal Department of Bioengineering Institute for Bioengineering and Biosciences (iBB) Instituto Superior Técnico University of Lisbon Portugal Institute for Bioengineering and Biosciences (iBB) and i4HB - Institute for Health and Bioeconomy Instituto Superior Técnico University of Lisbon Portugal Faculty of Computer Science Dalhousie University Halifax NS Canada School of Electrical Engineering and Computer Science Faculty of Engineering University of Ottawa ON Canada

Low-abundance microorganisms, often referred to as the “rare biosphere”, play a crucial role in ecosystem resistance and resilience, but remain challenging to study. One of the main difficulties lies in the lack of an appropriate definition of rare taxa. Most studies use relative abundance thresholds (e.g., 0.1 % relative abundance, per sample) to discern rare from abundant taxa within a microbial community. This is inappropriate because such thresholds are arbitrary and lack biological meaning. To solve this problem, we have proposed the utilization of unsupervised machine learning, through the ulrb (“Unsupervised Learning Definition of the Microbial Rare Biosphere”) algorithm, implemented as an R package (v0.1.8). This algorithm applies the partition around medoids (pam) algorithm to cluster taxa based on their abundance, in a community, for any number of samples. Based on the clusters, ulrb automatically classifies taxa into “rare”, “undetermined” or “abundant”, by default. Ulrb includes functions for all analytical steps necessary to define the rare biosphere. Specifically, we include four groups of functions: 1) process data of the user into the correct format for the ulrb algorithm;2) cluster taxa into abundance classifications;3) helper functions to evaluate detailed statistics of the clustering steps;and 4) visualization functions, focused on rank abundance curves and Silhouette scores, for assessment of clustering quality. In addition, ulrb allows the user to change the number of classifications obtained and includes options for detailed reporting. In this article, we describe the ulrb R package architecture, coding organization, and strategy. Furthermore, we use a 16S rRNA gene amplicon sequencing dataset from the Arctic Ocean to provide illustrative examples, with code, on how to use and explore ulrb capabilities. By explaining the architecture and implementation of ulrb, this study allows independent groups to integrate an abundance classification step i

关键词： K-medoids Microbial ecology Partition around medoids Rare biosphere Rarity Unsupervised machine learning