Article
Biology
Hang Su, Dong Zhao, Fanhua Yu, Ali Asghar Heidari, Yu Zhang, Huiling Chen, Chengye Li, Jingye Pan, Shichao Quan
Summary: This paper proposes an improved artificial bee colony algorithm (CCABC) and a multilevel thresholding image segmentation (MTIS) method based on CCABC. The performance of the CCABC algorithm is demonstrated through comparative experiments, and the improved image segmentation method is applied to the segmentation of COVID-19 X-ray images, achieving good results.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Ling Shen, Fuxing Liu, Li Huang, Guangyi Liu, Liqian Zhou, Lihong Peng
Summary: This study developed a Virus-Drug Association (VDA) identification framework combining various methods to screen potential anti-COVID-19 drugs, including remdesivir and ribavirin. The results showed that VDA-RWLRLS demonstrated superior performance and may contribute to preventing the transmission of COVID-19.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Information Systems
Ardhendu Sekhar, Soumen Biswas, Ranjay Hazra, Arun Kumar Sunaniya, Amrit Mukherjee, Lixia Yang
Summary: In the healthcare research community, IoMT is playing a transformative role in connecting the healthcare system with the future internet. Through IoMT-enabled CAD systems, health-related information is stored online and supportive data is provided to patients. This paper proposes a brain tumor classification method based on transfer learning and CNNs, achieving superior performance compared to existing models.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biochemical Research Methods
Jinxian Wang, Xuejun Liu, Siyuan Shen, Lei Deng, Hui Liu
Summary: In this paper, we proposed a deep learning model based on graph neural network and attention mechanism to identify drug combinations that can effectively inhibit the viability of specific cancer cells. The model, called DeepDDS, achieved better performance than other methods in predicting drug synergy. Additionally, we explored the interpretability of the model and found important chemical substructures of drugs. DeepDDS is considered an effective tool for prioritizing synergistic drug combinations for further experimental validation.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biology
Jianfu Xia, Zhifei Wang, Daqing Yang, Rizeng Li, Guoxi Liang, Huiling Chen, Ali Asghar Heidari, Hamza Turabieh, Majdi Mafarja, Zhifang Pan
Summary: This research aimed to construct a new intelligent diagnostic method that is accurate, fast, noninvasive, and cost-effective in distinguishing between complicated and uncomplicated appendicitis. The study analyzed the data of 298 patients with acute appendicitis and identified the most significant variables, then built a diagnostic model using an improved grasshopper optimization algorithm-based support vector machine.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biochemical Research Methods
Eduard Porta-Pardo, Victoria Ruiz-Serra, Samuel Valentini, Alfonso Valencia
Summary: The field of protein structure is undergoing a revolution, with advancements such as the AlphaFold database significantly improving our knowledge of human proteins. AlphaFold predictions enhance structural coverage and contribute to understanding important biomedical genes and mutations.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemical Research Methods
Lang Zhou, Tingze Feng, Shuangbin Xu, Fangluan Gao, Tommy T. Lam, Qianwen Wang, Tianzhi Wu, Huina Huang, Li Zhan, Lin Li, Yi Guan, Zehan Dai, Guangchuang Yu
Summary: The identification of conserved and variable regions in multiple sequence alignment is crucial for accelerating gene function understanding. ggmsa, an R package, provides various display methods to mine comprehensive sequence features, supports correlation analysis, and offers a new visualization method for genome alignment, aiding researchers in discovering MSA patterns and making decisions.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Chemistry, Multidisciplinary
Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng
Summary: This review introduces guidelines on utilizing deep learning methodologies and tools for drug repurposing, which is of great importance in drug development. The article summarizes the commonly used bioinformatics and pharmacogenomics databases for drug repurposing and discusses the recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. The applications of drug repurposing in fighting the COVID-19 pandemic are presented, along with an outline of future challenges.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2022)
Article
Biochemical Research Methods
Brennan Abanades, Guy Georges, Alexander Bujotzek, Charlotte M. Deane
Summary: In this study, the researchers developed a deep learning-based tool called ABlooper for predicting the structure of CDR loops in antibodies. ABlooper accurately predicts the structure of CDR-H3 loops, which are known for their sequence and structural variability. The tool provides high accuracy predictions and confidence estimates for each prediction.
Review
Chemistry, Multidisciplinary
Kyle R. Bryenton, Adebayo A. Adeleke, Stephen G. Dale, Erin R. Johnson
Summary: This article reviews the history of delocalization error in density-functional theory (DFT), provides conceptual interpretations and illustrative examples of its manifestations, and discusses approaches to reduce this error and its interplay with other shortcomings of popular DFAs.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2023)
Article
Biochemical Research Methods
Shixiang Wang, Yi Xiong, Longfei Zhao, Kai Gu, Yin Li, Fei Zhao, Jianfeng Li, Mingjie Wang, Haitao Wang, Ziyu Tao, Tao Wu, Yichao Zheng, Xuejun Li, Xue-Song Liu
Summary: UCSC Xena platform offers processed cancer omics data, while UCSCXenaShiny is an R Shiny package that allows users to quickly search, download, and explore the data. This tool provides important research opportunities for cancer researchers and clinicians with limited programming experience.
Article
Computer Science, Information Systems
Shuaiqi Liu, Xu Wang, Ling Zhao, Bing Li, Weiming Hu, Jie Yu, Yu-Dong Zhang
Summary: This paper proposes a deep learning model called 3DCANN for EEG emotion recognition. The model is able to extract spatio-temporal features from EEG signals and achieves superior performance over existing models in emotion classification.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Review
Biochemical Research Methods
Eun-Gyeong Park, Sung-Jin Pyo, Youxi Cui, Sang-Ho Yoon, Jin-Wu Nam
Summary: This review discusses the specific expression of long non-coding ribonucleic acids (lncRNAs) in tumor and immune cells, summarizes their regulatory functions at the cell type level, and highlights the application of single-cell RNA-sequencing (scRNA-seq) in studying the cell type-specific functions of lncRNAs in the tumor immune microenvironment (TIME).
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biology
Dalia Elebeedy, Ingy Badawy, Ayman Abo Elmaaty, Moustafa M. Saleh, Ahmed Kandeil, Aml Ghanem, Omnia Kutkat, Radwan Alnajjar, Ahmed Abd El Maksoud, Ahmed A. Al-karmalawy
Summary: This study evaluated the antiviral activities of six plant constituents against H1N1 virus, with Tanshinone IIA showing the most promising inhibitory activity and Salvianolic acid B demonstrating high affinities towards the surface glycoproteins of influenza A virus in in silico molecular docking.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Mathematical & Computational Biology
Nagaraja Gundluru, Dharmendra Singh Rajput, Kuruva Lakshmanna, Rajesh Kaluri, Mohammad Shorfuzzaman, Mueen Uddin, Mohammad Arifin Rahman Khan
Summary: Diabetic retinopathy is a severe health issue that can lead to vision loss and blindness. By utilizing a deep learning model with PCA and Harris hawks optimization algorithm, the feature extraction and classification process can be optimized, resulting in improved accuracy and precision.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Biology
Ishak Pacal, Ahmet Karaman, Dervis Karaboga, Bahriye Akay, Alper Basturk, Ufuk Nalbantoglu, Seymanur Coskun
Summary: This article presents deep learning-based methods for reliable computer-assisted polyp detection. The proposed methods improve the performance of object detection algorithms, enhance detection accuracy through data augmentation and transfer learning, and compare the effects of different activation functions on detection accuracy. The results demonstrate that the proposed methods outperform other studies in terms of real-time performance and polyp detection accuracy.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Mathematical & Computational Biology
Naveed Ahmad Khan, Osamah Ibrahim Khalaf, Carlos Andres Tavera Romero, Muhammad Sulaiman, Maharani A. Bakar
Summary: In this study, the intelligent computational strength of neural networks based on the backpropagated Levenberg-Marquardt algorithm is utilized to investigate the numerical solution of nonlinear multiorder fractional differential equations. The proposed algorithm is validated by comparing the approximate solutions with analytical solutions using different performance metrics. The results demonstrate the accuracy, robustness, and efficiency of the algorithm.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Biology
J. L. Gayathri, Bejoy Abraham, M. S. Sujarani, Madhu S. Nair
Summary: This paper presents a computer-aided detection model utilizing chest X-ray images for combating the COVID-19 pandemic. By utilizing pre-trained networks, sparse autoencoder, and a Feed Forward Neural Network (FFNN), the model achieves accurate detection of COVID-19.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Information Systems
Jun Chen, Guang Yang, Habib Khan, Heye Zhang, Yanping Zhang, Shu Zhao, Raad Mohiaddin, Tom Wong, David Firmin, Jennifer Keegan
Summary: In this paper, a new method called JAS-GAN is proposed for automated and accurate segmentation of unbalanced atrial targets from LGE CMR images. Compared with the state-of-the-art methods, JAS-GAN achieves better segmentation performance and proves to be effective for segmenting unbalanced atrial targets.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biology
Essam H. Houssein, Doaa A. Abdelkareem, Marwa M. Emam, Mohamed Abdel Hameed, Mina Younan
Summary: Skin cancer is a severe threat to individuals' health and safety. To improve the classification process, multilevel thresholding image segmentation is recommended for skin cancer images. This study proposes an efficient version of the opposition-based golden jackal optimizer (IGJO) algorithm to solve the multilevel thresholding problem. Experimental results show that the proposed algorithm outperforms other algorithms in segmentation metrics and effectively resolves the segmentation problem.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
