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Araújo R, Ramalhete L, Viegas A, Von Rekowski CP, Fonseca TAH, Calado CRC, Bento L. Simplifying Data Analysis in Biomedical Research: An Automated, User-Friendly Tool. Methods Protoc 2024; 7:36. [PMID: 38804330 PMCID: PMC11130801 DOI: 10.3390/mps7030036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/20/2024] [Accepted: 04/22/2024] [Indexed: 05/29/2024] Open
Abstract
Robust data normalization and analysis are pivotal in biomedical research to ensure that observed differences in populations are directly attributable to the target variable, rather than disparities between control and study groups. ArsHive addresses this challenge using advanced algorithms to normalize populations (e.g., control and study groups) and perform statistical evaluations between demographic, clinical, and other variables within biomedical datasets, resulting in more balanced and unbiased analyses. The tool's functionality extends to comprehensive data reporting, which elucidates the effects of data processing, while maintaining dataset integrity. Additionally, ArsHive is complemented by A.D.A. (Autonomous Digital Assistant), which employs OpenAI's GPT-4 model to assist researchers with inquiries, enhancing the decision-making process. In this proof-of-concept study, we tested ArsHive on three different datasets derived from proprietary data, demonstrating its effectiveness in managing complex clinical and therapeutic information and highlighting its versatility for diverse research fields.
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Affiliation(s)
- Rúben Araújo
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Luís Ramalhete
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- Blood and Transplantation Center of Lisbon, IPST—Instituto Português do Sangue e da Transplantação, Alameda das Linhas de Torres 117, 1769-001 Lisbon, Portugal
- iNOVA4Health—Advancing Precision Medicine, RG11: Reno-Vascular Diseases Group, NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
| | - Ana Viegas
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ESTeSL—Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Avenida D. João II, Lote 4.69.01, 1990-096 Lisbon, Portugal
- Neurosciences Area, Clinical Neurophysiology Unit, ULSSJ—Unidade Local de Saúde São José, Rua José António Serrano, 1150-199 Lisbon, Portugal
| | - Cristiana P. Von Rekowski
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Tiago A. H. Fonseca
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Cecília R. C. Calado
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
- Institute for Bioengineering and Biosciences (iBB), The Associate Laboratory Institute for Health and Bioeconomy–i4HB, Instituto Superior Técnico (IST), Universidade de Lisboa (UL), Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Luís Bento
- Intensive Care Department, ULSSJ—Unidade Local de Saúde São José, Rua José António Serrano, 1150-199 Lisbon, Portugal;
- Integrated Pathophysiological Mechanisms, CHRC—Comprehensive Health Research Centre, NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
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Bauer C, Stec K, Glintschert A, Gruden K, Schichor C, Or-Guil M, Selbig J, Schuchhardt J. BioMiner: Paving the Way for Personalized Medicine. Cancer Inform 2015; 14:55-63. [PMID: 26005322 PMCID: PMC4406277 DOI: 10.4137/cin.s20910] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Revised: 12/17/2014] [Accepted: 12/25/2014] [Indexed: 01/03/2023] Open
Abstract
Personalized medicine is promising a revolution for medicine and human biology in the 21st century. The scientific foundation for this revolution is accomplished by analyzing biological high-throughput data sets from genomics, transcriptomics, proteomics, and metabolomics. Currently, access to these data has been limited to either rather simple Web-based tools, which do not grant much insight or analysis by trained specialists, without firsthand involvement of the physician. Here, we present the novel Web-based tool “BioMiner,” which was developed within the scope of an international and interdisciplinary project (SYSTHER†) and gives access to a variety of high-throughput data sets. It provides the user with convenient tools to analyze complex cross-omics data sets and grants enhanced visualization abilities. BioMiner incorporates transcriptomic and cross-omics high-throughput data sets, with a focus on cancer. A public instance of BioMiner along with the database is available at http://systherDB.microdiscovery.de/, login and password: “systher”; a tutorial detailing the usage of BioMiner can be found in the Supplementary File.
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Affiliation(s)
- Chris Bauer
- Research and Development, MicroDiscovery GmbH, Berlin, Germany
| | - Karol Stec
- Research and Development, MicroDiscovery GmbH, Berlin, Germany
| | | | - Kristina Gruden
- Department for Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Christian Schichor
- Department of Neurosurgery, Klinikum der Ludwig-Maximilian-Universität München, Munich, Germany
| | - Michal Or-Guil
- Systems Immunology Lab, Department of Biology, Humboldt University, Berlin, Germany. ; Research Center ImmunoSciences, Charité University of Medicine Berlin, Berlin, Germany
| | - Joachim Selbig
- Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
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Kutmon M, van Iersel MP, Bohler A, Kelder T, Nunes N, Pico AR, Evelo CT. PathVisio 3: an extendable pathway analysis toolbox. PLoS Comput Biol 2015; 11:e1004085. [PMID: 25706687 PMCID: PMC4338111 DOI: 10.1371/journal.pcbi.1004085] [Citation(s) in RCA: 293] [Impact Index Per Article: 32.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 12/11/2014] [Indexed: 12/20/2022] Open
Abstract
PathVisio is a commonly used pathway editor, visualization and analysis software. Biological pathways have been used by biologists for many years to describe the detailed steps in biological processes. Those powerful, visual representations help researchers to better understand, share and discuss knowledge. Since the first publication of PathVisio in 2008, the original paper was cited more than 170 times and PathVisio was used in many different biological studies. As an online editor PathVisio is also integrated in the community curated pathway database WikiPathways. Here we present the third version of PathVisio with the newest additions and improvements of the application. The core features of PathVisio are pathway drawing, advanced data visualization and pathway statistics. Additionally, PathVisio 3 introduces a new powerful extension systems that allows other developers to contribute additional functionality in form of plugins without changing the core application. PathVisio can be downloaded from http://www.pathvisio.org and in 2014 PathVisio 3 has been downloaded over 5,500 times. There are already more than 15 plugins available in the central plugin repository. PathVisio is a freely available, open-source tool published under the Apache 2.0 license (http://www.apache.org/licenses/LICENSE-2.0). It is implemented in Java and thus runs on all major operating systems. The code repository is available at http://svn.bigcat.unimaas.nl/pathvisio. The support mailing list for users is available on https://groups.google.com/forum/#!forum/wikipathways-discuss and for developers on https://groups.google.com/forum/#!forum/wikipathways-devel.
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Affiliation(s)
- Martina Kutmon
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
- * E-mail: (MK); (CTE)
| | | | - Anwesha Bohler
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
| | | | - Nuno Nunes
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
| | - Alexander R. Pico
- Gladstone Institutes, San Francisco, California, United States of America
| | - Chris T. Evelo
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
- * E-mail: (MK); (CTE)
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