One file to share them all: Using the COMBINE Archive and the OMEX format to share all information about a modeling project

Background: With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result. Results: We describe the Open Modeling EXchange format (OMEX). Together with the use of other standard formats from the Computational Modeling in Biology Network (COMBINE), OMEX is the basis of the COMBINE Archive, a single file that supports the exchange of all the information necessary for a modeling and simulation experiment in biology. An OMEX file is a ZIP container that includes a manifest file, listing the content of the archive, an optional metadata file adding information about the archive and its content, and the files describing the model. The content of a COMBINE Archive consists of files encoded in COMBINE standards whenever possible, but may include additional files defined by an Internet Media Type. Several tools that support the COMBINE Archive are available, either as independent libraries or embedded in modeling software. Conclusions: The COMBINE Archive facilitates the reproduction of modeling and simulation experiments in biology by embedding all the relevant information in one file. Having all the information stored and exchanged at once also helps in building activity logs and audit trails. We anticipate that the COMBINE Archive will become a significant help for modellers, as the domain moves to larger, more complex experiments such as multi-scale models of organs, digital organisms, and bioengineering.Comment: 3 figures, 1 tabl

High Throughput Method to Quantify Anterior-Posterior Polarity of T-Cells and Epithelial Cells

The virologic synapse (VS), which is formed between a virus-infected and uninfected cell, plays a central role in the transmission of certain viruses, such as HIV and HTLV-1. During VS formation, HTLV-1-infected T-cells polarize cellular and viral proteins toward the uninfected T-cell. This polarization resembles anterior-posterior cell polarity induced by immunological synapse (IS) formation, which is more extensively characterized than VS formation and occurs when a T-cell interacts with an antigen-presenting cell. One measure of cell polarity induced by both IS or VS formation is the repositioning of the microtubule organizing center (MTOC) relative to the contact point with the interacting cell. Here we describe an automated, high throughput system to score repositioning of the MTOC and thereby cell polarity establishment. The method rapidly and accurately calculates the angle between the MTOC and the IS for thousands of cells. We also show that the system can be adapted to score anterior-posterior polarity establishment of epithelial cells. This general approach represents a significant advancement over manual cell polarity scoring, which is subject to experimenter bias and requires more time and effort to evaluate large numbers of cells

Systems Biology in ELIXIR: modelling in the spotlight

info:eu-repo/semantics/publishedVersio

Whole genome sequencing,molecular typing and in vivovirulence of OXA-48-producingEscherichia coli isolates includingST131 H30-Rx, H22 and H41subclones

Carbapenem-resistant Enterobacteriaceae, including the increasingly reported OXA-48 Escherichia coli producers, are an emerging public health threat worldwide. Due to their alarming detection in our healthcare setting and their possible presence in the community, seven OXA-48-producing, extraintestinal pathogenic E. coli were analysed by whole genome sequencing as well as conventional tools, and tested for in vivo virulence. As a result, five E. coli OXA-48-producing subclones were detected (O25:H4-ST131/PST43-fimH30-virotype E; O25:H4-ST131/PST9-fimH22-virotype D5, O16:H5-ST131/ PST506-fimH41; O25:H5-ST83/PST207 and O9:H25-ST58/PST24). Four ST131 and one ST83 isolates satisfied the ExPEC status, and all except the O16:H5 ST131 isolate were UPEC. All isolates exhibited local inflammatory response with extensive subcutaneous necrosis but low lethality when tested in a mouse sepsis model. The blaOXA-48 gene was located in MOBP131/IncL plasmids (four isolates) or within the chromosome (three ST131 H30-Rx isolates), carried by Tn1999-like elements. All, except the ST83 isolate, were multidrug-resistant, with additional plasmids acting as vehicles for the spread of various resistance genes. This is the first study to analyse the whole genome sequences of blaOXA-48-positive ST131, ST58 and ST83 E. coli isolates in conjunction with experimental data, and to evaluate the in vivo virulence of blaOXA-48 isolates, which pose an important challenge to patient management

Systems Biology in ELIXIR: modelling in the spotlight

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR\u27s future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

The dynamic stability and nonlinear resonance of a flexible connecting rod: Continuous parameter model

The transverse vibrations of a flexible connecting rod in an otherwise rigid slider-crank mechanism are considered. An analytical approach using the method of multiple scales is adopted and particular emphasis is placed on nonlinear effects which arise from finite deformations. Several nonlinear resonances and instabilities are investigated, and the influences of important system parameters on these resonances are examined in detail.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43330/1/11071_2004_Article_BF00162233.pd

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

© 2024 Niarakis, Ostaszewski, Mazein, Kuperstein, Kutmon, Gillespie, Funahashi, Acencio, Hemedan, Aichem, Klein, Czauderna, Burtscher, Yamada, Hiki, Hiroi, Hu, Pham, Ehrhart, Willighagen, Valdeolivas, Dugourd, Messina, Esteban-Medina, Peña-Chilet, Rian, Soliman, Aghamiri, Puniya, Naldi, Helikar, Singh, Fernández, Bermudez, Tsirvouli, Montagud, Noël, Ponce-de-Leon, Maier, Bauch, Gyori, Bachman, Luna, Piñero, Furlong, Balaur, Rougny, Jarosz, Overall, Phair, Perfetto, Matthews, Rex, Orlic-Milacic, Gomez, De Meulder, Ravel, Jassal, Satagopam, Wu, Golebiewski, Gawron, Calzone, Beckmann, Evelo, D’Eustachio, Schreiber, Saez-Rodriguez, Dopazo, Kuiper, Valencia, Wolkenhauer, Kitano, Barillot, Auffray, Balling, Schneider and the COVID-19 Disease Map Community. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.The author(s) declare financial support was received for the research, authorship, and/or publication of this article. AN acknowledges support from SANOFI-AVENTIS R&D via the CIFRE contract, n° 2020/0766. MK, FH, NP, FE, and CE acknowledge the support of the ZonMw COVID-19 programme (Grant No. 10430012010015). JD Spanish Ministry of Science and Innovation (Grant no. PID2020-117979RB-I00) and Instituto de Salud Carlos III (Grant no. IMP/00019). MAi, KK, FS: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 251654672 - TRR 161 and under Germany’s Excellence Strategy - EXC 2117 - 422037984. FM: “5 per 1000–2021” grant of the Italian Ministry of Health (Grant No. 5M-2021-23683787) and European Commission with HORIZON programme, BY-COVID project (Grant No. 101046203—BY-COVID). National Institute for Infectious Diseases Lazzaro Spallanzani–IRCCS received financial support from the Italian Ministry of Health grant “Ricerca Corrente”. JP, LF: IMI2-JU grants, resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA [GA: 777365 eTRANSAFE], and the EU H2020 Programme [GA:964537 RISKHUNT3R]; Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya; Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, “A way to make Europe”). AMo, MP and AV acknowledge the support of the European Commission under the INFORE project (H2020-ICT-825070) and the PerMedCoE (H2020-ICT-951773). Contributions by TH and BLP were supported by NIH grant #R35GM119770 to TH. MaGo acknowledges funding from Deutsche Forschungsgemeinschaft (DFG) through grants no. 442326535 (NFDI4Health) and 451265285 (NFDI4Health Task Force COVID-19), from the European Commission through the Horizon 2020 framework program under grant no. 825843 (EU-STANDS4PM) and through the Digital Europe program under grant no. 101083771 (EDITH), as well as from the Klaus Tschira Foundation. AL acknowledges support from the Intramural Research Program of the National Library of Medicine (NLM), National Institutes of Health (NIH).Peer reviewe

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies