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Data analysis guidelines for single‑cell RNA‑seq in biomedical studies and clinical applications

Military Medical Research 2023年第4期10卷 529-553页

作者： Min Su Tao Pan Qiu‑Zhen Chen Wei‑Wei Zhou Yi Gong Gang Xu Huan‑Yu Yan Si Li Qiao‑Zhen Shi Ya Zhang Xiao He Chun‑Jie Jiang Shi‑Cai Fan Xia Li Murray J.Cairns Xi Wang Yong‑Sheng Li State Key Laboratory of Reproductive Medicine Nanjing Medical UniversityNanjing 211166China College of Biomedical Information and Engineering the First Affiliated Hospital of Hainan Medical UniversityHainan Medical UniversityHaikou 571199HainanChina College of Bioinformatics Science and Technology Harbin Medical UniversityHarbin 150081HeilongjiangChina Department of Immunology Nanjing Medical UniversityNanjing 211166China Department of Laboratory Medicine Women and Children’s Hospital of Chongqing Medical UniversityChongqing 401174China Baylor College of Medicine HoustonTX 77030USA Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110GuangdongChina School of Biomedical Sciences and Pharmacy Faculty of Health and Medicinethe University of NewcastleUniversity DriveCallaghanNSW 2308Australia Precision Medicine Research Program Hunter Medical Research InstituteNew Lambton HeightsNSW 2305Australia

The application of single-cell RNA sequencing(scRNA-seq)in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic *** the expansion of capacity for high-throughput scRNA-seq,including clinical samples,the analysis of these huge volumes of data has become a daunting prospect for researchers entering this ***,we review the workflow for typical scRNA-seq data analysis,covering raw data processing and quality control,basic data analysis applicable for almost all scRNA-seq data sets,and advanced data analysis that should be tailored to specific scientific *** summarizing the current methods for each analysis step,we also provide an online repository of software and wrapped-up scripts to support the *** and caveats are pointed out for some specific analysis tasks and *** hope this resource will be helpful to researchers engaging with scRNA-seq,in particular for emerging clinical applications.

关键词： Single-cell RNA-sequencing(scRNA-seq) Data analysis biomedical research Clinical applications

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High-Resolution Imaging of Human Cancer Proteins Using Microprocessor Materials

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ChemBioChem 2022年第17期23卷 e202200310-e202200310页

作者： Solares, Maria J. Jonaid, G.M. Luqiu, William Y. Berry, Samantha Khadela, Janki Liang, Yanping Evans, Madison C. Pridham, Kevin J. Dearnaley, William J. Sheng, Zhi Kelly, Deborah F. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park 16802 PA United States Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park 16802 PA United States Department of Biomedical Engineering Pennsylvania State University University Park 16802 PA United States Center for Structural Oncology Pennsylvania State University University Park 16802 PA United States Department of Electrical and Computer Engineering Duke University Durham 27708 NC United States Fralin Biomedical Research Institute at VTC Virginia Tech Roanoke 24016 VA United States

Mutations in tumor suppressor genes, such as Tumor Protein 53 (TP53), are heavily implicated in aggressive cancers giving rise to gain- and loss-of-function phenotypes. While individual domains of the p53 protein have been studied extensively, structural information for full-length p53 remains incomplete. Functionalized microprocessor chips (microchips) with properties amenable to electron microscopy permitted us to visualize complete p53 assemblies for the first time. The new structures revealed p53 in an inactive dimeric state independent of DNA binding. Residues located at the protein-protein interface corresponded with modification sites in cancer-related hot spots. Changes in these regions may amplify the toxic effects of clinical mutations. Taken together, these results contribute advances in technology and imaging approaches to decode native protein models in different states of activation. © 2022 Wiley-VCH GmbH.

关键词： cancer electron microscopy microchips p53, molecular modeling

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Single-cell RNA-sequencing and subcellular spatial transcriptomics facilitate the translation of liver microphysiological systems for regulatory application

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Journal of Pharmaceutical Analysis 2023年第7期13卷 691-693页

作者： Dan Li Zhou Fang Qiang Shi Nicholas Zhang Binsheng Gong Weida Tong Ahmet F.Coskun Joshua Xu Division of Bioinformatics and Biostatistics National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory UniversityAtlantaGA30332USA Machine Learning Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Division of Systems Biology National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Interdisciplinary Bioengineering Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Parker H.Petit Institute for Bioengineering and Bioscience Georgia Institute of TechnologyAtlantaGA30332USA

Reducing the use of animal models in drug development and safety assessment has long been supported by the *** and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million *** ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug *** animal testing has been the traditional method for assessing the safety and efficacy of drugs.

关键词： money utilizing testing

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Diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG Systems Review

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IEEE Journal of biomedical and Health Informatics 2023年第8期27卷 3830-3843页

作者： He, Congying Chen, Yu-Yi Phang, Chun-Ren Stevenson, Cory Chen, I-Ping Jung, Tzyy-Ping Ko, Li-Wei Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Applied Arts National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San DiegoCA90093 United States National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan

Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FDA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems. © 2023 IEEE.

关键词： Electroencephalography

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PFAS compounds PFOA and Gen X are teratogenic to sea urchin embryos

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Developmental biology 2025年 525卷 139-154页

作者： Alexandra T Lion Sophie M Bodine Kelley R McCutcheon Mayank Ghogale Santhan Chandragiri Deema Abayawardena Bikram D Shrestha Abigail Descoteaux Kathryn Alvarez J'nesse A Balkman Breelyn Cocke Athula H Wikramanayake Jennifer Schlezinger Joyce Y Wong Vivek N Prakash Cynthia A Bradham Molecular Biology Cell Biology and Biochemistry Program Boston University Boston MA USA. Biology Department Boston University Boston MA USA. Bioinformatics Program Boston University Boston MA USA. Department of Physics University of Miami Coral Gables FL USA. Department of Biology University of Miami Coral Gables FL USA. Molecular Biology Cell Biology and Biochemistry Program Boston University Boston MA USA Biological Design Center College of Engineering Boston University Boston MA USA. Environmental Health Boston University Boston MA USA. Department of Biomedical Engineering Boston University Boston MA USA. Department of Physics University of Miami Coral Gables FL USA Department of Biology University of Miami Coral Gables FL USA Department of Marine Biology and Ecology University of Miami Miami FL USA. Biology Department Boston University Boston MA USA Bioinformatics Program Boston University Boston MA USA Biological Design Center College of Engineering Boston University Boston MA USA. Electronic address: cbradham@bu.edu.

Per-and polyfluorinated substances (PFAS) are synthetic compounds used in the production of fluoropolymer coatings found in products such as non-stick pans, clothing, cosmetics, and food packaging. These highly persistent molecules are known as "forever chemicals" since they neither degrade environmentally nor break down enzymatically within biological systems. PFAS compounds readily contaminate water sources, and as a result, certain PFAS molecules have bioaccumulated in exposed species including humans. The purpose of this study was to define the effect of two PFAS molecules, the ostensibly more toxic perfluorooctanoic acid (PFOA) and the more recent, reportedly safer chemical hexafluoropropylene oxide dimer acid (Gen X), on the development of Lytechinus variegatus sea urchin embryos. We examined the effects of PFOA and Gen X on development and patterning using morphological analysis, immunostaining, HCR-FISH, and Particle Image Velocimetry (PIV). The results show that both PFAS compounds are teratogenic to sea urchin embryos. PFOA and Gen X each function at different intervals during development and provoke distinct phenotypic and gene expression outcomes. Despite beliefs that Gen X would be a safer alternative, our findings indicate that Gen X has earlier and more severe effects on endomesoderm and dorsal-ventral axis specification, neural development and function, and pattern formation compared to PFOA. These results illustrate the dangerous teratogenic potential of environmentally accumulating PFAS like Gen X, underscoring the negative ecological implications that accompany continuing commercial and industrial use of PFAS in the absence of remediation strategies.

关键词： Gen X PFOA cilia neural teratogen

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Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation

arXiv

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arXiv 2025年

作者： Tang, Sophia Zhang, Yinuo Tong, Alexander Chatterjee, Pranam Department of Biomedical Engineering Duke University United States Management and Technology Program University of Pennsylvania United States Center of Computational Biology Duke-NUS Medical School Singapore Mila Quebec AI Institute Canada Université de Montréal Canada Department of Computer Science Duke University United States Department of Biostatistics and Bioinformatics Duke University United States

Flow matching in the continuous simplex has emerged as a promising strategy for DNA sequence design, but struggles to scale to higher simplex dimensions required for peptide and protein generation. We introduce Gumbel-Softmax Flow and Score Matching, a generative framework on the simplex based on a novel Gumbel-Softmax interpolant with a time-dependent temperature. Using this interpolant, we introduce Gumbel-Softmax Flow Matching by deriving a parameterized velocity field that transports from smooth categorical distributions to distributions concentrated at a single vertex of the simplex. We alternatively present Gumbel-Softmax Score Matching which learns to regress the gradient of the probability density. Our framework enables high-quality, diverse generation and scales efficiently to higher-dimensional simplices. To enable training-free guidance, we propose Straight-Through Guided Flows (STGFlow), a classifier-based guidance method that leverages straight-through estimators to steer the unconditional velocity field toward optimal vertices of the simplex. STGFlow enables efficient inference-time guidance using classifiers pre-trained on clean sequences, and can be used with any discrete flow method. Together, these components form a robust framework for controllable de novo sequence generation. We demonstrate state-of-the-art performance in conditional DNA promoter design, sequence-only protein generation, and target-binding peptide design for rare disease treatment. © 2025, CC BY-NC-ND.

关键词： Velocity distribution

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Development of label-free triboelectric nanosensors as screening platforms for anti-tumor drugs

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Nano Energy 2024年 125卷

作者： Cheng, Yu-Ying Ganguly, Anindita Cheng, Yi-Yun Ortiz, Christopher Llynard D. Pal, Arnab Shah, Pramod Kaswan, Kuldeep Yang, Lee-Wei Lin, Zong-Hong Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan Internet of Senses Research Center National Tsing Hua University Hsinchu30013 Taiwan Praexisio Taiwan Inc. New Taipei221425 Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu300044 Taiwan Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program Institute of Biological Chemistry Academia Sinica Taipei115 Taiwan Department of Chemistry National Tsing Hua University Hsinchu300044 Taiwan International Intercollegiate PhD Program National Tsing Hua University Hsinchu300044 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu300044 Taiwan Biomedical Artificial Intelligence PhD Program National Tsing Hua University Hsinchu300044 Taiwan Physics Division National Center for Theoretical Sciences Taipei Taiwan

This study introduces a general label-free drug screening platform with potential to support high-throughput drug screening for any protein target. Its innovation lies in quantifying the affinity of molecule-molecule interactions via voltage output variation, which achieves unprecedented selectivity and sensitivity. It combines computational analysis complemented by experimental substantiation with a solid-liquid triboelectric nanosensor. Owing to its high binding affinity, FKBP-rapamycin is used as a model system to demonstrate the platform's sensitivity. Subsequently, the research is extended to study drug interactions with an oncogenic protein ATG4B. The findings unveil the binding of S130 and Tioconazole to ATG4B, a critical cysteine protease involved in autophagy, while revealing that Dexamethasone does not bind ATG4B. This binding exerts a specific inhibitory effect on autophagic flux and triggers cancer cell apoptosis. The results support the previously verified inhibitory effects of these drugs and the effectiveness of a newly developed self-powered drug screening platform, leveraging the principles of solid-liquid contact electrification. This approach adeptly confronts enduring challenges in traditional drug development methods where biochemical assays need to be designed for each individual protein target or only time-consuming and concentration-demanding molecular interaction measurements were made available. © 2024 Elsevier Ltd

关键词： Nanosensors

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jen-Chien Yu Chun-Chieh Yang John Reuben Gilbert Rou-Jun Liu Yen-Jen Oyang Meng-Han Yang Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan ROC Master Program in Statistics National Taiwan University Taipei Taiwan ROC Department of Computer Science & Information Engineering National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset.

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Peer Teaching as bioinformatics Training Strategy: Incentives, Challenges, and Benefits

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Medical Reference Services Quarterly 2022年第1期41卷 13-25页

作者： Rahman, Nur-Taz Meyer, Caitlin Thakral, Durga Cai, Wesley L. Chen, Ann T. Obaid, Razib Garcia-Milian, Rolando Bioinformatics Support Program Research and Education Services Harvey Cushing/John Hay Whitney Medical Library Yale University New Haven CT United States Department of Dermatology Yale School of Medicine New Haven CT United States Department of Pathology Yale School of Medicine New Haven CT United States Department of Biomedical Engineering Yale University New Haven CT United States RARAF Radiological Research Accelerator Facility Nevis Laboratory Columbia University Irvington NY United States

bioinformatics is essential for basic and clinical research. Peer-to-peer (P2P) teaching was used to respond to the bioinformatics training needs at a research-intensive institution. In addition to the data collected from the workshops, personal experiences of the teachers were used to understand incentives, challenges, and benefits of P2P teaching. Developing communication skills such as confidence in teaching, explaining complex concepts, and better understanding of topics benefited P2P teachers. Lack of time and classroom management were identified as major challenges. Hence, P2P teaching can be beneficial not only for bioinformatics trainees but also as a professional development opportunity for peer teachers. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

关键词： bioinformatics computational biology data education peer teaching training

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

Predicting Microsatellite Instability from Histology Images ...

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IEEE Symposium on bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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