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iTReX: Interactive exploration of mono- and combination therapy dose response profiling data

Pharmacological Research 2022年 175卷 105996-105996页

作者： ElHarouni, Dina Berker, Yannick Peterziel, Heike Gopisetty, Apurva Turunen, Laura Kreth, Sina Stainczyk, Sabine A. Oehme, Ina Pietiäinen, Vilja Jäger, Natalie Witt, Olaf Schlesner, Matthias Oppermann, Sina Bioinformatics and Omics Data Analytics German Cancer Research Center (DKFZ) Heidelberg Germany Hopp Children's Cancer Center (KiTZ) Heidelberg Germany Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Clinical Cooperation Unit Pediatric Oncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Division of Neuroblastoma Genomics German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Department of Pediatric Oncology Hematology Immunology and Pulmonology Heidelberg University Hospital Heidelberg Germany Biomedical Informatics Data Mining and Data Analytics Faculty of Applied Computer Science and Medical Faculty University of Augsburg Augsburg Germany

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application's ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at https://*** © 2021 The Authors

关键词： Asymmetric sensitivity scoring Differential combination sensitivity scoring Drug target networks Interactive drug screen analysis Personalized medicine Therapy response profiling and exploration

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Deep and handcrafted feature supported diabetic retinopathy detection: A study

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Procedia Computer Science 2023年 218卷 2675-2683页

作者： Seifedine Kadry Rubén González Crespo Enrique Herrera-Viedma Sujatha Krishnamoorthy Venkatesan Rajinikanth Faculty of Applied Computing and Technology Noroff University College Kristiansand 94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja 26006 Andalusian Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai 600119 Tamil Nadu India

The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) supported eye screening is one of the ophthalmological practices. This work proposed a Deep-Learning Procedure (DLP) to recognize Diabetic Retinopathy (DR) in FI. The proposed work presents the experimental work with different DLP methods found in the literature. This work is executed with two modes; (i) DR detection using conventional deep-features and (ii) DR discovery using deep ensemble features. To demonstrate this work, 1800 fundus images (900 regular and 900 DR class) are considered for the assessment, and the advantage of proposed plan is confirmed using various performance metrics. The experimental outcome of this study confirms that the AlexNet-based detection provides a better detection (>96%), and the deep ensemble features of AlexNet, VGG16, and ResNet18 provide a detection accuracy of >98% on the chosen FRI database.

关键词： Eye abnormality Diabetic retinopathy Fundus imaging Deep-Learning Classification

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Development of a Predictive Model for Potentially Inappropriate Medications in Older Patients with Cardiovascular Disease

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Drugs & aging 2024年第8期41卷 675-683页

作者： Chun-Ying Lee Yun-Shiuan Chuang Chew-Teng Kor Yi-Ting Lin Yu-Hsiang Tsao Pei-Ru Lin Hui-Min Hsieh Mei-Chiou Shen Ya-Ling Wang Tzu-Jung Fang Yen-Tze Liu Department of Family Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan. Research Center for Precision Environmental Medicine Kaohsiung Medical University Kaohsiung Taiwan. Center for Big Data Research Kaohsiung Medical University Kaohsiung Taiwan. Big Data Center Changhua Christian Hospital Changhua Taiwan. Faculty of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. Department of Public Health College of Health Sciences Kaohsiung Medical University Kaohsiung Taiwan. Division of Medical Statistics and Bioinformatics Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Taiwan. Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Taiwan. Department of Community Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan. Department of Pharmacy Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan. School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. Division of Geriatrics and Gerontology Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan. Big Data Center Changhua Christian Hospital Changhua Taiwan. 144084@cch.org.tw. Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan. 144084@cch.org.tw. Department of Family Medicine Changhua Christian Hospital Changhua 500 Taiwan. 144084@cch.org.tw. Graduate Institute of Clinical Medicine College of Medicine National Chung Hsing University Taichung Taiwan. 144084@cch.org.tw.

BACKGROUND:Older patients with cardiovascular disease (CVD) are highly susceptible to adverse drug reactions due to age-related physiological changes and the presence of multiple comorbidities, polypharmacy, and potentially inappropriate medications (PIMs). OBJECTIVE:This study aimed to develop a predictive model to identify the use of PIMs in older patients with CVD. METHODS:data from 2012 to 2021 from the Changhua Christian Hospital Clinical Research database (CCHRD) and the Kaohsiung Medical University Hospital Research database (KMUHRD) were analyzed. Participants over the age of 65 years with CVD diagnoses were included. The CCHRD data were randomly divided into a training set (80% of the database) and an internal validation set (20% of the database), while the KMUHRD data served as an external validation set. The training set was used to construct the prediction models, and both validation sets were used to validate the proposed models. RESULTS:A total of 48,569 patients were included. Comprehensive data analysis revealed significant associations between the use of PIMs and clinical factors such as total cholesterol, glycated hemoglobin (HbA1c), creatinine, and uric acid levels, as well as the presence of diabetes, hypertension, and cerebrovascular accidents. The predictive models demonstrated moderate power, indicating the importance of these factors in assessing the risk of PIMs. CONCLUSIONS:This study developed predictive models that improve understanding of the use of PIMs in older patients with CVD. These models may assist clinicians in making informed decisions regarding medication safety.

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The outcomes of thoracoscopic decortication between fungal empyema and bacterial empyema

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BMC Infectious Diseases 2023年第1期23卷 8-8页

作者： Cheng, Ya-Fu Chen, Chun-Min Chen, Yi-Ling Cheng, Ching-Yuan Huang, Chang-Lun Hung, Wei-Heng Wang, Bing-Yen Division of Thoracic Surgery Department of Surgery Changhua Christian Hospital Changhua No. 135 Nanxiao St. Changhua City 500 Taiwan Big Data Center Epidemiology and Biostatistics Center Changhua Christian Hospital Changhua City Taiwan Surgery Clinical Research Center Changhua Christian Hospital Changhua City Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan School of Medicine Chung Shan Medical University Taichung Taiwan School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Center for General Education Ming Dao University Changhua City Taiwan

Background: Fungal empyema is an uncommon disease and is associated with a high mortality rate. Surgical intervention is suggested in stage II and III empyema. However, there were no studies that reported the outcomes of surgery for fungal empyema. Methods: This study is a retrospective analysis in a single institute. Patients with empyema thoracis who underwent thoracoscopic decortication between January 2012 and December 2021 were included in the study. We separated the patients into a fungal empyema group and a bacterial empyema group according to culture results. We used 1:3 propensity score matching to reduce selection bias. Results: There were 1197 empyema patients who received surgery. Of these, 575 patients showed positive culture results and were enrolled. Twenty-eight patients were allocated to the fungal empyema group, and the other 547 patients were placed in the bacterial empyema group. Fungal empyema showed significantly longer intensive care unit stay (16 days vs. 3 days, p = 0.002), longer median ventilator usage duration (20.5 days vs. 3 days, p = 0.002), longer hospital stay duration (40 days vs. 17.5 days, p < 0.001) and a higher 30-day mortality rate (21.4% vs. 5.9%, p < 0.001). Fungal empyema revealed significantly poorer 1-year survival rate than bacterial empyema before matching (p < 0.001) but without significant difference after matching. Conclusions: The fungal empyema patients had much worse surgical outcomes than the bacterial empyema patients. Advanced age and high Charlson Comorbidity Index score are independent predictors for poor prognosis. Prompt surgical intervention combined with the use of antifungal agents was the treatment choice for fungal empyema. © 2023, The Author(s).

关键词： Bacteria Empyema thoracis Fungus Outcomes Surgery

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Mapping Emergency Medicine data to the Observational Medical Outcomes Partnership Common data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency data Registry

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JACEP Open 2025年第1期6卷 100016-100016页

作者： Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States

Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency data Registry (CEDR) to the Observational Medical Outcomes Partnership Common data Model (OMOP-CDM). Methods: We employed a structured approach using a custom-built comparison matrix. This matrix facilitated the alignment of CEDR data fields with the corresponding elements in the OMOP-CDM schema. Each field was evaluated for compatibility, with categorization into 3 distinct types: direct matches, fields requiring transformation, and fields with no OMOP-CDM equivalent. The mapping process was informed by consultations with the Observational Health data Sciences and Informatics community forums and was guided by existing documentation and best practices in data harmonization. We performed descriptive analyses, quantifying the extent of direct matches and identifying the specific transformations needed for each CEDR-CDM field to ensure compliance with the OMOP-CDM model. Results: Our analysis indicates a high degree of compatibility between CEDR and OMOP, with over 90% (244/269) of CEDR fields being successfully mapped. Specifically, 173 fields had direct matches, whereas 71 required transformations. Challenges identified include addressing fields unique to CEDR with no OMOP-CDM equivalent and managing the transformations required for proper alignment. Conclusion: The OMOP-CDM presents a promising framework for standardizing emergency medicine data, thereby enhancing future query automation, analytics, and cross-institutional collaboration. Despite the potential challenges in capturing unique CEDR fields and addressing necessary transformations, most emergency department data can be standardized within the OMOP-CDM, fostering broader insights and applications in research and public health. © 2024 The Author(s)

关键词： databases electronic health records emergency service informatics opioid/adverse effects quality of health care registries

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Exploring the regulatory function of the N-terminal domain of SARS-CoV-2 spike protein through molecular dynamics simulation

arXiv

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arXiv 2021年

作者： Li, Yao Wang, Tong Zhang, Juanrong Shao, Bin Gong, Haipeng Wang, Yusong Liu, Siyuan Liu, Tie-Yan MOE Key Laboratory of Bioinformatics School of Life Sciences Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Structural Biology Tsinghua University Beijing100084 China Microsoft Research Asia Beijing China School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China

SARS-CoV-2 is what has caused the COVID-19 pandemic. Early viral infection is mediated by the SARS-CoV-2 homo-trimeric Spike (S) protein with its receptor binding domains (RBDs) in the receptor-accessible state. We performed molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs). Our study reveals that the NTD acts as a "wedge" and plays a crucial regulatory role in the conformational changes of the S protein. The complete RBD structural transition is allowed only when the neighboring NTD that typically prohibits the RBD’s movements as a wedge detaches and swings away. Based on this NTD "wedge" model, we propose that the NTD-RBD interface should be a potential drug target. Copyright © 2021, The Authors. All rights reserved.

关键词： SARS

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Transcriptome analysis reveals a de novo DNA element that may interact with chromatin-associated proteins in Plasmodium berghei during erythrocytic development

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Scientific reports 2025年第1期15卷 18621页

作者： Adaobi Okafor Yagoub Adam Benedikt Brors Ezekiel Adebiyi Applied Bioinformatics German Cancer Research Center (DKFZ) Im Neuenheimer Feld 280 69120 Heidelberg Germany. Faculty of Biosciences Heidelberg University Im Neuenheimer Feld 234 69120 Heidelberg Germany. Covenant University Bioinformatics Research (CUBRe) Covenant University Ota 112233 Ogun State Nigeria. Applied Bioinformatics German Cancer Research Center (DKFZ) Im Neuenheimer Feld 280 69120 Heidelberg Germany. e.adebiyi@dkfz-heidelberg.de. Covenant University Bioinformatics Research (CUBRe) Covenant University Ota 112233 Ogun State Nigeria. e.adebiyi@dkfz-heidelberg.de. African Center of Excellence in Bioinformatics & Data Intensive Science Makerere University 10218 Kampala Uganda. e.adebiyi@dkfz-heidelberg.de. Institute of Infectious Diseases (IDI) Makerere University 10218 Kampala Uganda. e.adebiyi@dkfz-heidelberg.de.

The life cycle of Plasmodium parasites involves intricate, multistage processes that are tightly regulated by stage-specific transcription factors. These factors bind to regulatory regions within gene promoters, enabling the precise expression of genes required for each developmental stage. Despite the importance of these transcriptional mechanisms, our understanding remains limited, particularly in the rodent model organism P. berghei. To address this, we conducted a genome-wide analysis of RNA-Seq data from different developmental stages of P. berghei by initially integrating data from human malaria parasites P. falciparum and P. vivax. We identified unique transcriptional signatures across Plasmodium species. Our analysis of P. berghei revealed stage-specific gene sets clustered by expression profiles and predicted regulatory motifs involved in their control. We interpreted these motifs using known binding sites for eukaryotic transcription factors including ApiAP2 proteins. Additionally, we expanded the annotation of the AGGTAA motif which resembles a de novo motif linked to erythrocytic development in P. falciparum, and identified its potential interacting proteins including members of the PfMORC and GCN5 complexes. This study enhances our understanding of gene regulation in P. berghei and provides new insights into the transcriptional dynamics underlying Plasmodium development.

关键词： Plasmodium berghei Plasmodium falciparum Plasmodium vivax ApiAP2 proteins RNA-Seq Regulatory motifs

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Comparative assessment of the Sikun 2000 sequencing platform for whole genome sequencing

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Scientific reports 2025年第1期15卷 19070页

作者： Keya Cai Sibin Li Meng Pan Hui Lu Liang Wang Shengquan Fang Lingzhi Gou Jiang Tang Yan Kong Li Zhao Yongyong Ren Sikun Life Science Company Limited ZhengZhou 450016 China. Institute of Bioinformatics Shanghai Academy of Experimental Medicine Shanghai 201203 China. SJTU-Yale Joint Center for Biostatistics and Data Science Technical Center for Digital Medicine National Center for Translational Medicine Shanghai Jiao Tong University Shanghai 200240 China. Department of Bioinformatics and Biostatistics School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai 200240 China. Department of Gastroenterology Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Shanghai University of Traditional Chinese Medicine Shanghai 200437 China. Sikun Life Science Company Limited ZhengZhou 450016 China. zhaoli@***. SJTU-Yale Joint Center for Biostatistics and Data Science Technical Center for Digital Medicine National Center for Translational Medicine Shanghai Jiao Tong University Shanghai 200240 China. yongyong.ren@***. Institute of Bioinformatics Shanghai Academy of Experimental Medicine Shanghai 201203 China. yongyong.ren@***.

DNA sequencing technology has significantly advanced over the past five decades, particularly with the introduction of next-generation sequencing (NGS) platforms like Illumina's NovaSeq. In October 2023, Sikun introduced the Sikun 2000, a desktop NGS platform designed for rapid, cost-effective sequencing with up to 200 Gb of data per run. This study is the first to evaluate the performance of the Sikun 2000 in whole genome sequencing (WGS) and compares it with the Illumina NovaSeq 6000 and NovaSeq X platforms using five well-characterized human Genomes in a Bottle dataset. Results show that the Sikun 2000 performs competitively in variant detection, particularly excelling in single nucleotide variant accuracy. It also demonstrated a higher sequencing depth and lower proportion of low-quality reads than the NovaSeq platforms. However, its performance in insertion-deletion (Indel) detection was slightly lower than that of NovaSeq platforms. Overall, the Sikun 2000 is a qualified sequencing platform for WGS, and further evaluation in clinical and research applications is required as data continues to accumulate.

关键词： Sikun 2000 Variation detection Whole genome sequencing

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Recording provenance of workflow runs with RO-Crate

arXiv

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arXiv 2023年

作者： Leo, Simone Crusoe, Michael R. Rodríguez-Navas, Laura Sirvent, Raül Kanitz, Alexander De Geest, Paul Wittner, Rudolf Pireddu, Luca Garijo, Daniel Fernández, José M. Colonnelli, Iacopo Gallo, Matej Ohta, Tazro Suetake, Hirotaka Capella-Gutierrez, Salvador de Wit, Renske Kinoshita, Bruno P. Soiland-Reyes, Stian CA Pula Italy Vrije Universiteit Amsterdam Amsterdam Netherlands DTL Projects Netherlands Forschungszentrum Jülich Germany Barcelona Supercomputing Center Barcelona Spain Biozentrum University of Basel Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland VIB Data Core Gent Belgium Faculty of Informatics Masaryk University Brno Czech Republic Institute of Computer Science Masaryk University Brno Czech Republic BBMRI-ERIC Graz Austria Ontology Engineering Group Universidad Politécnica de Madrid Madrid Spain Computer Science Department Università degli Studi di Torino Torino Italy Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Shizuoka Japan Institute for Advanced Academic Research Chiba University Chiba Japan Sator Incorporated Tokyo Japan Department of Computer Science The University of Manchester Manchester United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and *** to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain. © 2023, CC BY.

关键词： Workflow management

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Transit Functions and Pyramid-Like Binary Clustering Systems

arXiv

引用

arXiv 2022年

作者： Changat, Manoj Shanavas, Ameera Vaheeda Stadler, Peter F. Department of Futures Studies University of Kerala IN Trivandrum695 581 India Bioinformatics Group Department of Computer Science Interdisciplinary Center for Bioinformatics Universität Leipzig Härtelstraße 16-18 LeipzigD-04107 Germany Halle-Jena-Leipzig Competence Center for Scalable Data Services and Solutions Dresden-Leipzig Leipzig Research Center for Civilization Diseases Centre for Biotechnology and Biomedicine Leipzig University Universität Leipzig Max Planck Institute for Mathematics in the Sciences Inselstraße 22 LeipzigD-04103 Germany Institute for Theoretical Chemistry University of Vienna Währingerstrasse 17 WienA-1090 Austria Facultad de Ciencias Universidad National de Colombia Bogotá Colombia Santa Fe Insitute 1399 Hyde Park Rd. Santa FeNM87501 United States

Binary clustering systems are closely related to monotone transit functions. An interesting class are pyramidal transit functions defined by the fact that their transit sets form an interval hypergraph. We investigate here properties of transit function R, such as union-closure, that are sufficient to ensure that R is at least weakly pyramidal. Necessary conditions for pyramidal transit functions are derived from the five forbidden configurations in Tucker's characterization of interval hypergraphs. The first corresponds to β-acyclicity, also known as total balancedness, for which we obtain three alternative characterizations. For monotonous transit functions, the last forbidden configuration becomes redundant, leaving us with characterization of pyramidal transit functions in terms of four additional conditions. © 2022, CC BY-SA.

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