Article
Chemistry, Multidisciplinary
Frank Neese
Summary: The latest version 5.0 of the ORCA quantum chemistry program suite represents a significant improvement in performance, numerical robustness, functionality, and user friendliness.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Biochemical Research Methods
Givanna H. Putri, Simon Anders, Paul Theodor Pyl, John E. Pimanda, Fabio Zanini
Summary: HTSeq 2.0 provides an expanded application programming interface, including a new representation for sparse genomic data, enhancements for htseq-count to accommodate single-cell omics, a new script for data using cell and molecular barcodes, improved documentation, testing and deployment, bug fixes, and Python 3 support.
Article
Biochemical Research Methods
Ryan R. Wick, Kathryn E. Holt
Summary: Polypolish is a new short-read polisher that uses all-per-read alignments to fix errors in repeat sequences that other polishers cannot. It performed well in benchmarking tests and introduced minimal errors during the polishing process.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biology
Ailiang Qi, Dong Zhao, Fanhua Yu, Ali Asghar Heidari, Zongda Wu, Zhennao Cai, Fayadh Alenezi, Romany F. Mansour, Huiling Chen, Mayun Chen
Summary: This paper focuses on the study of COVID-19 X-ray image segmentation technology. A new multilevel image segmentation method based on the swarm intelligence algorithm is proposed, along with a designed image segmentation model. Experimental results show that the proposed model achieves more stable and superior segmentation results at different threshold levels.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biochemical Research Methods
Chaoran Chen, Sarah Nadeau, Michael Yared, Philippe Voinov, Ning Xie, Cornelius Roemer, Tanja Stadler
Summary: The CoV-Spectrum website provides support for identifying and tracking new SARS-CoV-2 variants, with flexible mutation search capabilities and analysis on various data sources to understand characteristics and transmission of different variants.
Review
Biology
Yizhou Chen, Xu-Hua Yang, Zihan Wei, Ali Asghar Heidari, Nenggan Zheng, Zhicheng Li, Huiling Chen, Haigen Hu, Qianwei Zhou, Qiu Guan
Summary: This paper provides a comprehensive review and analysis of medical image augmentation, focusing on the advantages of different augmentation models, loss functions, and evaluation metrics. It explores the potential role of augmented models in limited training set scenarios and discusses the limitations and research directions in this field. The research shows that this field is still actively developing.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biochemical Research Methods
Haoyu Zhang, Quan Zou, Ying Ju, Chenggang Song, Dong Chen
Summary: This study presents a novel model based on sequence distance matrix and support vector machine (SVM) for predicting DNA 6mA modification. The model achieved high accuracy rates and correlation coefficients on rice and mouse data, showing significant advantages over traditional machine learning methods.
CURRENT BIOINFORMATICS
(2022)
Article
Biology
Hang Su, Dong Zhao, Hela Elmannai, Ali Asghar Heidari, Sami Bourouis, Zongda Wu, Zhennao Cai, Wenyong Gui, Mayun Chen
Summary: COVID-19 is spreading globally, and the diagnosis is usually based on examining chest radiographs. Manual processing of the images is not efficient and accurate enough. To improve the efficiency, this research proposes a multilevel thresholding image segmentation method based on an enhanced multiverse optimizer. The method achieves better segmentation results and can help medical organizations process COVID-19 chest radiography effectively.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Information Systems
Hang Li, Keping Yu, Bin Liu, Chaosheng Feng, Zhiguang Qin, Gautam Srivastava
Summary: The Internet of Health Things (IoHT) refers to uniquely identifiable devices connected to the Internet that can communicate with each other. This concept plays a crucial role in smart health monitoring and improvement systems, with cybersecurity being a top priority. This article proposes a novel access policy expression method and constructs a flexible and efficient encryption scheme to ensure data security in the IoHT.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Review
Chemistry, Multidisciplinary
Cherumuttathu H. Suresh, Geetha S. Remya, Puthannur K. Anjalikrishna
Summary: The MESP topology analysis is widely used for the interpretation and prediction of chemical reactivity, providing valuable information about bonded regions, electron-rich regions, and intermolecular interactions. The mapping of MESP topology is achieved by computing backward difference data and Hessian matrix elements at critical points.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Biology
Keli Hu, Liping Zhao, Sheng Feng, Shengdong Zhang, Qianwei Zhou, Xiaozhi Gao, Yanhui Guo
Summary: In this paper, a novel method called NeutSS-PLP is proposed for polyp region extraction in colonoscopy images using a short connected saliency detection network with neutrosophic enhancement. Experimental results on two public datasets demonstrate the effectiveness of the proposed method for polyp extraction.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biochemical Research Methods
Nadav Brandes, Dan Ofer, Yam Peleg, Nadav Rappoport, Michal Linial
Summary: Self-supervised deep language modeling has achieved unprecedented success with natural language tasks, and the authors introduce a new deep language model called ProteinBERT specifically designed for proteins, which efficiently handles long sequences and achieves near or even better performance than other methods, providing an effective framework for rapid training of protein predictors.
Article
Computer Science, Information Systems
Hu Xiong, Chuanjie Jin, Mamoun Alazab, Kuo-Hui Yeh, Hanxiao Wang, Thippa Reddy Gadekallu, Weizheng Wang, Chunhua Su
Summary: This paper proposes an efficient and large-scale batch verification scheme based on ECDSA, utilizing group testing technology to improve the efficiency of identifying invalid signatures. The application of this scheme in Bitcoin and Hyperledger Fabric is analyzed and shown to be effective and supportive. Comprehensive simulation results demonstrate that our protocol outperforms related ECDSA batch verification schemes.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biochemical Research Methods
Feiyue Sun, Jianqiang Sun, Qi Zhao
Summary: Metabolism is the process of replacing old substances with new substances in organisms, which is important for maintaining human life, body growth, and reproduction. Researchers have found that the concentrations of certain metabolites in patients are different from those in healthy individuals. Traditional biological experiments are time-consuming and costly, so there is an urgent need for a new computational method to identify the relationships between metabolites and diseases. In this study, a new deep learning algorithm called GCNAT is proposed to predict potential associations between disease-related metabolites. The algorithm achieves better results than existing predictive methods and can be a useful tool for biomedical research in the future.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Chemistry, Multidisciplinary
Samer Gozem, Anna I. Krylov
Summary: A molecule's spectrum serves as a unique fingerprint encoding information about its structure and electronic properties, acting as a molecular ID. Quantum chemistry calculations play a crucial role in interpreting spectra, but modeling the spectra often requires additional steps considering electronic and nuclear degrees of freedom and experimental specifics. The ezSpectra suite, comprising ezFCF and ezDyson, offers tools for calculating Franck-Condon factors and absolute cross-sections for various processes.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Review
Biology
Mohammad Shehab, Laith Abualigah, Qusai Shambour, Muhannad A. Abu-Hashem, Mohd Khaled Yousef Shambour, Ahmed Izzat Alsalibi, Amir H. Gandomi
Summary: Machine learning methods have been extensively applied in the medical field to enhance the reliability and accuracy of diagnostic systems. This survey provides a comprehensive review of the standard technologies and discusses five major medical applications of machine learning.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Review
Biology
Zohaib Salahuddin, Henry C. Woodruff, Avishek Chatterjee, Philippe Lambin
Summary: AI is increasingly used in clinical applications for diagnosis and treatment decisions, with deep neural networks showing equal or better performance than clinicians. However, their lack of interpretability calls for the development of methods to ensure their trustworthiness. Nine different types of interpretability methods have been identified for understanding deep learning models in medical image analysis, with ongoing research on improving interpretability and evaluation methods for deep neural networks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Mathematical & Computational Biology
Zulqurnain Sabir
Summary: In this study, a computational method combining artificial neural networks (ANNs) and genetic algorithm (GA) is used to numerically analyze a three-dimensional nonlinear food chain system. The accuracy and reliability of this method are validated through comparisons and statistical representations.
INTERNATIONAL JOURNAL OF BIOMATHEMATICS
(2022)
Article
Computer Science, Information Systems
Zhiwei Guo, Yu Shen, Shaohua Wan, Wen-Long Shang, Keping Yu
Summary: In this paper, a hybrid intelligence-driven medical image recognition framework combining deep learning with conventional machine learning is proposed to solve the issue of remote patient diagnosis in smart cities. Experimental results reveal that the framework improves recognition accuracy by approximately two to three percent compared to traditional methods.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biochemical Research Methods
Fengcheng Li, Ying Zhou, Ying Zhang, Jiayi Yin, Yunqing Qiu, Jianqing Gao, Feng Zhu
Summary: Mass spectrometry-based proteomic technique is essential in studying biological processes. However, current statistical frameworks neglect the reproducibility among identified features. Thus, developing a tool to identify reproducible and generalizable proteomic signatures is crucial.
BRIEFINGS IN BIOINFORMATICS
(2022)
