Article
Multidisciplinary Sciences
Shawn Zheng Kai Tan, Huseyin Kir, Brian D. Aevermann, Tom Gillespie, Nomi Harris, Michael J. Hawrylycz, Nikolas L. Jorstad, Ed S. Lein, Nicolas Matentzoglu, Jeremy A. Miller, Tyler S. Mollenkopf, Christopher J. Mungall, Patrick L. Ray, Raymond E. A. Sanchez, Brian Staats, Jim Vermillion, Ambika Yadav, Yun Zhang, Richard H. Scheuermann, David Osumi-Sutherland
Summary: Large-scale single-cell 'omics profiling is being used to define a complete catalogue of brain cell types. However, organizing this catalogue and linking cell types to supporting data has been a problem. This study presents a schema that solves these issues and applies it to build a data-linked extension to the Cell Ontology representing cell types in the Primary Motor Cortex of humans, mice, and marmosets.
Article
Multidisciplinary Sciences
Ana Kostovska, Jasmin Bogatinovski, Saso Dzeroski, Dragi Kocev, Pance Panov
Summary: Multilabel classification is a machine learning task that aims to label examples with multiple labels simultaneously. It is gaining increasing interest from the machine learning community. Ensuring proper benchmarking is crucial for further development, and this can be achieved by following data management standards such as FAIR and TRUST principles. We introduce an ontology-based online catalogue of multilabel classification datasets, providing comprehensive descriptions and information.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Vinicius Costa Lima, Rui Pedro Charters Lopes Rijo, Filipe Andrade Bernardi, Marcio Eloi Colombo Filho, Francisco Barbosa-Junior, Felipe Carvalho Pellison, Rafael Mello Galliez, Afranio Lineu Kritski, Domingos Alves
Summary: Clinical research outcomes rely on the accurate definition of research protocols, data collection strategies, and data management plans. Electronic Data Capture Systems mitigate resource challenges and provide a reliable environment for health research, promoting result dissemination and data reusability.
SCIENTIFIC REPORTS
(2023)
Article
Biology
Bart Nijsse, Peter J. Schaap, Jasper J. Koehorst
Summary: The life sciences are a major source of scientific data. Reusing and connecting these data can lead to new concepts and insights. However, the availability of easy-to-adopt implementations that fulfill the needs of data producers is limited. In response, the FAIR Data Station, a lightweight application written in Java, has been developed to support researchers in managing research metadata according to the FAIR principles. It includes modules for generating metadata templates, validating recorded values, and converting metadata into RDF format.
Article
Geosciences, Multidisciplinary
Stephanie R. James, Nathan Leon Foks, Burke J. Minsley
Summary: The paper proposes a new geophysical standard, GS convention, that utilizes the well-established NetCDF file format and the CF metadata convention. With the accompanying open-source Python package GSPy, methods and workflows for building GS-standardized NetCDF files, importing/exporting data, preparing input files, and visualizing data and models are provided.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Biochemistry & Molecular Biology
Barbara Zdrazil, Eloy Felix, Fiona Hunter, Emma J. Manners, James Blackshaw, Sybilla Corbett, Marleen de Veij, Harris Ioannidis, David Mendez Lopez, Juan F. Mosquera, Maria Paula Magarinos, Nicolas Bosc, Ricardo Arcila, Tevfik Kiziloren, Anna Gaulton, A. Patricia Bento, Melissa F. Adasme, Peter Monecke, Gregory A. Landrum, Andrew R. Leach
Summary: ChEMBL is a curated resource of bioactive molecules with drug-like properties. It has evolved significantly in size and diversity of data types over time. The inclusion of new datasets has expanded the bioactivity data available and added new features to ChEMBL.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Wanda Marsolek, Sarah J. Wright, Hoa Luong, Susan M. Braxton, Jake Carlson, Sophia Lafferty-Hess
Summary: Data curation is a series of actions to ensure research data are fit for purpose and can be discovered and reused. Researchers value and find satisfaction in data curation, as it adds value to the data sharing process, is worth the effort, and increases their confidence in sharing data.
Article
Biochemistry & Molecular Biology
Yongbiao Xue, Yiming Bao, Zhang Zhang, Wenming Zhao, Jingfa Xiao, Shun-min He, Guoqing Zhang, Yixue Li, Guoping Zhao, Runsheng Chen, Yingke Ma, Meili Chen, Cuiping Li, Shuai Jiang, Dong Zou, Zheng Gong, Xue-tong Zhao, Yanqing Wang, Junwei Zhu, Shuhui Song, Yunchao Ling, Yiwei Wang, Jiaxin Yang, Xinhao Zhuang, Guangya Duan, Gangao Wu, Xiaoning Chen, Dongmei Tian, Zhaohua Li, Yan-ling Sun, Zhenglin Du, Lili Hao, Yuan Gao, Bixia Tang, Yadong Zhang, Hao Zhang, Zaichao Zhang, Qiheng Qian, Zhewen Zhang, Hailong Kang, Tianhao Huang, Zhiqiang Xia, Xincheng Zhou, Jin-quan Chao, Zhonghuang Wang, Jun-wei Zhu, Sisi Zhang, Weimin Tian, Wenquan Wang, Song Wu, Yue Huang, Mochen Zhang, Guoliang Wang, Xin-chang Zheng, Wenting Zong, Wei Zhao, Peiqi Xing, Rujiao Li, Zhaoqi Liu, Mingming Lu, Fengchun Yang, Jialin Mai, Qianwen Gao, Xiaowei Xu, Hongyu Kang, Li Hou, Yunfei Shang, Qiheng Qain, Jie Liu, Meiye Jiang, Congfan Bu, Jinyue Wang, Jingyao Zeng, Jiao Li, Siyu Pan, Hongen Kang, Xinxuan Liu, Shiqi Lin, Na Yuan, Peilin Jia, Xinchang Zheng, Yanling Sun, Zhuang Xiong, Fei Yang, Xu Chen, Tingting Chen, Caixia Yu, Lili Dong, Shuang Zhai, Yubin Sun, Qiancheng Chen, Xiaoyu Yang, Xin Zhang, Zhengqi Sang, Yonggang Wang, Yilin Zhao, Huanxin Chen, Li Lan, Yan-qing Wang, Anke Wang, Yaokai Jia, Xuetong Zhao, Yitong Pan, Xiaonan Liu, Rongqin Zhang, Yi Wang, Lina Ma, Xufei Teng, Lun Li, Na Li, Ying Cui, Tong Jin, Enhui Jin, Tao Zhang, Tianyi Xu, Ming Chen, Guangyi Niu, Rong Pan, Tongtong Zhu, Yuan Chu, Jian Sang, Yuanpu Zhang, Zhennan Wang, Yuan-sheng Zhang, Qiliang Yao, Xinran Zhang, Xutong Guo, Zhao Li, Lin Liu, Changrui Feng, Yuxin Qin, Wei Jing, Sicheng Luo, Tong-tong Zhu, Yuansheng Zhang, Zis-han Wu, Qianpeng Li, Pei Liu, Yongqing Sun, Zhuojing Fan, Wen-ming Zhao, Wen-Kang Shen, An-Yuan Guo, Zhixiang Zuo, Jian Ren, Xinxin Zhang, Yun Xiao, Xia Li, Dan Liu, Chi Zhang, Yu Xue, Zheng Zhao, Tao Jiang, Wanying Wu, Fangqing Zhao, Xianwen Meng, Yujie Gou, Miaomiao Chen, Di Peng, Hao Luo, Feng Gao, Wanshan Ning, Wan Liu, Ruifang Cao, Guo-qing Zhang, Yuxiang Wei, Chun-Jie Liu, Gui-Yan Xie, Hao Yuan, Tianhan Su, Yong E. Zhang, Chenfen Zhou, Pengyu Wang, Yincong Zhou, Guoji Guo, Qiong Zhang, Shanshan Fu, Xiaodan Tan, Dachao Tang, Weizhi Zhang, Mei Luo, Yubin Xie, Ya-Ru Miao, Xinhe Huang, Zihao Feng, Xingyu Liao, Xin Gao, Jianxin Wang, Guiyan Xie, Chunhui Yuan, Dechang Yang, Feng Tian, Ge Gao, Wenyi Wu, Cheng Han, Qinghua Cui, Chunfu Xiao, Chuan-Yun Li, XiaoTong Luo, Qing Tang
Summary: The National Genomics Data Center (NGDC) of the China National Center for Bioinformation (CNCB) provides database resources to support global academic and industrial communities. The NGDC constantly expands and updates core database resources by archiving big data, conducting integrative analysis, and providing value-added curation. New database resources have been developed for infectious diseases and microbiology, cancer-trait association, and tropical plants. Additionally, resources for the monkeypox virus and SARS-CoV-2 have been newly constructed and regularly updated. All resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Computer Science, Information Systems
Elena Parmiggiani, Nana Kwame Amagyei, Steinar Kornelius Selebo Kollerud
Summary: Data curation is crucial for data reusability, and it requires three practices: retrospective, present-oriented, and future-looking, to support data reuse. Anticipatory generification is essential for the sustainable development of environmental data infrastructures.
EUROPEAN JOURNAL OF INFORMATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Eduardo Xamena, Nelida Beatriz Brignole, Ana Gabriela Maguitman
Summary: This study analyzes several relevance propagation models from the perspective of complex network theory, including structural properties like Characteristic path length, Clustering coefficient and Degree distribution. The analysis reveals interesting points about the Small-world and Scale-free structure of some relevance propagation models, while other connectivity and centrality measures provide further insight into the topology of relevance. Additionally, visualizations of the k-core decomposition of different relevance propagation models complement the analysis, showcasing the generalizability of the methodology proposed in the study.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Biochemistry & Molecular Biology
Noemi del Toro, Anjali Shrivastava, Eliot Ragueneau, Birgit Meldal, Colin Combe, Elisabet Barrera, Livia Perfetto, Karyn How, Prashansa Ratan, Gautam Shirodkar, Odilia Lu, Balint Meszaros, Xavier Watkins, Sangya Pundir, Luana Licata, Marta Iannuccelli, Matteo Pellegrini, Maria Jesus Martin, Simona Panni, Margaret Duesbury, Sylvain D. Vallet, Juri Rappsilber, Sylvie Ricard-Blum, Gianni Cesareni, Lukasz Salwinski, Sandra Orchard, Pablo Porras, Kalpana Panneerselvam, Henning Hermjakob
Summary: IntAct is a curated database of molecular interactions derived from scientific literature, containing over one million binary interactions curated by twelve global partners. The IMEx curation policy emphasizes fine-grained data and curation model to capture essential experimental details for interpretation of the molecular interaction data. Recently, IntAct has introduced a completely redeveloped website to present data in a more user-friendly and detailed way.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Geochemistry & Geophysics
Valentin Isheyskiy, Evgeny Martinyskin, Sergey Smirnov, Anton Vasilyev, Kirill Knyazev, Timur Fatyanov
Summary: This paper provides a structured analysis of measurement while drilling (MWD) data processing and verification methods, focusing on clean data selection to build a parent training database for machine learning algorithms. The main goal is to create a trainable machine learning algorithm to estimate rock characteristics, predict optimal drilling and blasting parameters, and blasting results. This research is part of a series on using MWD technology for quality management in mining drilling and blasting operations.
Article
Environmental Sciences
Menberu B. Meles, Eleonora M. C. Demaria, Philip Heilman, David C. Goodrich, Mark A. Kautz, Gerardo Armendariz, Carl Unkrich, Haiyan Wei, Anandraj Thiyagaraja Perumal
Summary: This article describes the development of new quality control procedures for experimental watersheds, using hydrologic principles to analyze the relationships between rainfall and runoff events. The evaluation of these tools showed improved data accuracy and reliability for experimental watershed datasets.
Article
Radiology, Nuclear Medicine & Medical Imaging
David A. Wood, Sina Kafiabadi, Aisha Al Busaidi, Emily L. Guilhem, Jeremy Lynch, Matthew K. Townend, Antanas Montvila, Martin Kiik, Juveria Siddiqui, Naveen Gadapa, Matthew D. Benger, Asif Mazumder, Gareth Barker, Sebastian Ourselin, James H. Cole, Thomas C. Booth
Summary: The study aimed to build a deep learning model to extract labels from neuroradiology reports and assign them to corresponding examinations, overcoming a bottleneck in computer vision model development. The model achieved accurate classification for all categories when tested against reference-standard report labels, but saw a drop in performance when tested against reference-standard image labels.
EUROPEAN RADIOLOGY
(2022)
Article
Biochemical Research Methods
Almut Heinken, Stefania Magnusdottir, Ronan M. T. Fleming, Ines Thiele
Summary: DEMETER is a tool that can efficiently refine thousands of draft genome-scale reconstructions simultaneously, ensuring adherence to quality standards, agreement with available experimental data, and refinement of pathways based on manually refined genome annotations.
Article
Rheumatology
Burcu Ayoglu, Michele Donato, Daniel E. Furst, Leslie J. Crofford, Ellen Goldmuntz, Lynette Keyes-Elstein, Judith James, Susan Macwana, Maureen D. Mayes, Peter McSweeney, Richard A. Nash, Keith M. Sullivan, Beverly Welch, Ashley Pinckney, Rong Mao, Lorinda Chung, Purvesh Khatri, Paul J. Utz
Summary: Results from the SCOT clinical trial showed that HSCT had significant benefits over CTX in patients with systemic sclerosis. The objective of this study was to test the hypothesis that transplantation stabilizes the autoantibody repertoire in patients with favorable clinical outcomes. Analysis of autoantibody profiles revealed significant differences between HSCT and CTX-treated patients, suggesting that HSCT alters the autoantibody repertoire while CTX treatment does not.
ANNALS OF THE RHEUMATIC DISEASES
(2023)
Article
Oncology
Oihane Erice, Shruthi Narayanan, Iker Feliu, Rodrigo Entrialgo-Cadierno, Antonia Malinova, Caterina Vicentini, Elizabeth Guruceaga, Pietro Del fi No, Marija Trajkovic-Arsic, Haritz Moreno, Karmele Valencia, Ester Blanco, Irati Macaya, Daniel Ohlund, Purvesh Khatri, Fernando Lecanda, Aldo Scarpa, Jens T. Siveke, Vincenzo Corbo, Mariano Ponz-Sarvise, Silve Vicent
Summary: In this study, the expression of LAMC2 in PDAC and its regulated network were investigated, with the aim of identifying potential therapies. It was found that LAMC2 was consistently upregulated in PDAC and associated with tumor grade and survival. The LAMC2-regulated network contained downstream effectors shared by the KRAS signaling pathway, and the inhibition of LAMC2 or AXL showed a synergistic antiproliferative effect in combination with MEK1/2 inhibitors in PDAC models.
CLINICAL CANCER RESEARCH
(2023)
Article
Medicine, General & Internal
Maryam Shojaei, Uan- Chen, Uros Midic, Simone Thair, Sally Teoh, Anthony McLean, Timothy E. E. Sweeney, Matthew Thompson, Oliver Liesenfeld, Purvesh Khatri, Benjamin Tang
Summary: IMX-BVN-1, a 29-host mRNA classifier, accurately differentiates bacterial and viral infections in patients with suspected influenza, providing potential clinical utility in acute healthcare settings.
EUROPEAN JOURNAL OF CLINICAL INVESTIGATION
(2023)
Article
Biology
Lydia J. Wilson, Frederico C. Kiffer, Daniel C. Berrios, Abigail Bryce-Atkinson, Sylvain V. Costes, Olivier Gevaert, Bruno F. E. Matarese, Jack Miller, Pritam Mukherjee, Kristen Peach, Paul N. Schofield, Luke T. Slater, Britta Langen
Summary: The era of high-throughput techniques has generated large amounts of data in the medical and research fields. Machine intelligence (MI) approaches are being used to overcome limitations in processing, analyzing, and interpreting these massive data sets. The 67th Annual Meeting of the Radiation Research Society featured a symposium on MI approaches, highlighting recent advancements in radiation sciences and their clinical applications. This article summarizes three presentations on metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.
INTERNATIONAL JOURNAL OF RADIATION BIOLOGY
(2023)
Article
Gastroenterology & Hepatology
Lawrence Bai, Denis Dermadi, Laurynas Kalesinskas, Mai Dvorak, Sarah E. Chang, Ananthakrishnan Ganesan, Samuel J. S. Rubin, Alex Kuo, Peggie Cheung, Michele Donato, Paul J. Utz, Aida Habtezion, Purvesh Khatri
Summary: This study quantified histone modifications at a single-cell resolution in patients with inflammatory bowel disease (IBD) and discovered substantial heterogeneity across immune cell types. Specific histone modifications associated with gene transcription were identified, and a subset of NK cells was found to be associated with higher levels of C-reactive protein. These findings open new avenues for investigating the association between histone modifications and IBD pathology using other epigenomic tools.
JOURNAL OF CROHNS & COLITIS
(2023)
Review
Biology
Mehwish Zafar, Muhammad Imran Sharif, Muhammad Irfan Sharif, Seifedine Kadry, Syed Ahmad Chan Bukhari, Hafiz Tayyab Rauf
Summary: The skin is the largest organ in the human body and skin cancer is one of the most dangerous types of cancer. Abnormal cell growth in human skin cells can be caused by various pathological variations and genetic disorders. Early diagnosis is crucial due to the slow development and high mortality rate of skin cancer. Numerous computer-aided diagnosis systems utilizing deep learning, machine learning, and computer vision approaches have been proposed for the recognition of skin cancer. This research provides a comprehensive review of the methodologies, techniques, and approaches used for examining skin lesions, with a focus on the challenges and obstacles in analyzing complex and rare features.
Article
Oncology
Chen Chen, June Ho Shin, Zhuoqing Fang, Kevin Brennan, Nina B. Horowitz, Kathleen L. Pfaff, Emma L. Welsh, Scott J. Rodig, Olivier Gevaert, Or Gozani, Ravindra Uppaluri, John B. Sunwoo
Summary: In head and neck squamous cell carcinoma (HNSCC), inactivating mutations in the histone methyltransferase NSD1 disproportionately contribute to tumor development and immune exclusion. Understanding the NSD1-mediated mechanism and targeting the histone-modifying enzyme KDM2A could enhance T-cell infiltration and suppress tumor growth in HNSCC.
Correction
Multidisciplinary Sciences
Prabhu S. Arunachalam, Madeleine K. D. Scott, Thomas Hagan, Chunfeng Li, Yupeng Feng, Florian Wimmers, Lilit Grigoryan, Meera Trisal, Venkata Viswanadh Edara, Lilin Lai, Sarah Esther Chang, Allan Feng, Shaurya Dhingra, Mihir Shah, Alexandra S. Lee, Sharon Chinthrajah, Sayantani B. Sindher, Vamsee Mallajosyula, Fei Gao, Natalia Sigal, Sangeeta Kowli, Sheena Gupta, Kathryn Pellegrini, Gregory Tharp, Sofia Maysel-Auslender, Sydney Hamilton, Hadj Aoued, Kevin Hrusovsky, Mark Roskey, Steven E. Bosinger, Holden T. Maecker, Scott D. Boyd, Mark M. Davis, Paul J. Utz, Mehul S. Suthar, Purvesh Khatri, Kari C. Nadeau, Bali Pulendran
Article
Biochemistry & Molecular Biology
Alexander H. H. Thieme, Yuanning Zheng, Gautam Machiraju, Chris Sadee, Mirja Mittermaier, Maximilian Gertler, Jorge L. Salinas, Krithika Srinivasan, Prashnna Gyawali, Francisco Carrillo-Perez, Angelo Capodici, Maximilian Uhlig, Daniel Habenicht, Anastassia Loeser, Maja Kohler, Maximilian Schuessler, David Kaul, Johannes Gollrad, Jackie Ma, Christoph Lippert, Kendall Billick, Isaac Bogoch, Tina Hernandez-Boussard, Pascal Geldsetzer, Olivier Gevaert
Summary: A deep-learning algorithm, MPXV-CNN, was developed to identify skin lesions caused by the mpox virus for early detection and mitigation. It demonstrated a sensitivity of 0.83-0.91 and a specificity of 0.965-0.898 across different datasets. The algorithm was robust in classifying lesions on various skin tones and body regions, and a web-based app was developed for patient guidance.
Article
Multidisciplinary Sciences
Kexin Ding, Mu Zhou, He Wang, Olivier Gevaert, Dimitris Metaxas, Shaoting Zhang
Summary: To enhance computational pathology, we introduce a large-scale synthetic pathological image dataset paired with nucleus annotations, called SNOW. By applying off-the-shelf image generator and nuclei annotator, SNOW offers a cost-effective means to improve model performance. Results show that models trained on synthetic data are competitive and expand the use of synthetic images for data-driven clinical tasks.
Article
Computer Science, Artificial Intelligence
Sandra Steyaert, Marija Pizurica, Divya Nagaraj, Priya Khandelwal, Tina Hernandez-Boussard, Andrew J. Gentles, Olivier Gevaert
Summary: Cancer diagnosis and treatment decisions often focus on a single data source. However, there is a need for effective multimodal fusion approaches to integrate complementary data types. The current technological advances and introduction of deep learning have the potential to address the challenges of data integration in cancer research.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Dermatology
Michelle Phung, Vijaytha Muralidharan, Veronica Rotemberg, Roberto Andres Novoa, Albert Sean Chiou, Christoph Y. Sadee, Bailie Rapaport, Kiana Yekrang, Jared Bitz, Olivier Gevaert, Justin Meng Ko, Roxana Daneshjou
Summary: Recent developments in artificial intelligence research have led to the increased use of algorithms for detecting malignancies in clinical and dermoscopic images of skin diseases. Gathering training and testing data is crucial for these methods. This paper explores the best practices and challenges in collecting skin images and data for translational artificial intelligence research, including ethics, image acquisition, labeling, curation, and storage. The aim is to enhance malignancy detection using artificial intelligence by facilitating intentional data collection and collaboration between dermatologists and data scientists.
JOURNAL OF INVESTIGATIVE DERMATOLOGY
(2023)
Article
Multidisciplinary Sciences
Yuanning Zheng, Francisco Carrillo-Perez, Marija Pizurica, Dieter Henrik Heiland, Olivier Gevaert
Summary: In this study, two deep learning models were used to predict the transcriptional subtypes and prognosis of glioblastoma (GBM) cells from histology images. The results showed consistent associations between spatial cellular organization and patient prognosis. The study also confirmed that transcriptional heterogeneity and cell-state plasticity are key factors in the development of therapeutic resistance in GBM.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Irati Macaya, Marta Roman, Connor Welch, Rodrigo Entrialgo-Cadierno, Marina Salmon, Alba Santos, Iker Feliu, Joanna Kovalski, Ines Lopez, Maria Rodriguez-Remirez, Sara Palomino-Echeverria, Shane M. Lonfgren, Macarena Ferrero, Silvia Calabuig, Iziar A. Ludwig, David Lara-Astiaso, Eloisa Jantus-Lewintre, Elizabeth Guruceaga, Shruthi Narayanan, Mariano Ponz-Sarvise, Antonio Pineda-Lucena, Fernando Lecanda, Davide Ruggero, Purvesh Khatri, Enrique Santamaria, Joaquin Fernandez-Irigoyen, Irene Ferrer, Luis Paz-Ares, Matthias Drosten, Mariano Barbacid, Ignacio Gil-Bazo, Silve Vicent
Summary: Drug combinations are essential for overcoming resistance to targeted therapies in cancer treatment. By utilizing a gene signature-driven drug repurposing approach and a pairwise pharmacological screen, the authors identified a synergistic drug combination for KRAS-mutated lung adenocarcinoma. The combination treatment shows cytotoxic response and involves inhibition of the PKC inhibitor target AURKB.
NATURE COMMUNICATIONS
(2023)
Article
Genetics & Heredity
Rushika Pandya, Yudong D. He, Timothy E. Sweeney, Yehudit Hasin-Brumshtein, Purvesh Khatri
Summary: This study identified a conserved host response in nasal samples that can be used for diagnosis and ruling out viral infection in symptomatic patients. By analyzing 1555 samples, a classifier based on 33 genes was developed, which can accurately distinguish viral acute respiratory illnesses from healthy controls and non-viral ARIs.