Computational and structural biotechnology journal最新文献

{"title":"Rapid intraoperative amplicon sequencing of CNS tumor markers","authors":"Maximilian Evers ,&nbsp;Björn Brändl ,&nbsp;Christian Rohrandt ,&nbsp;Carolin Kubelt-Kwamin ,&nbsp;Franz-Josef Müller ,&nbsp;Dominik Danso ,&nbsp;André Maicher ,&nbsp;Gaojianyong Wang ,&nbsp;Sönke Friedrichsen ,&nbsp;Stephan Kolkenbrock","doi":"10.1016/j.csbj.2024.11.007","DOIUrl":"10.1016/j.csbj.2024.11.007","url":null,"abstract":"<div><div>Currently, central nervous system tumors are diagnosed with an integrated diagnostic approach that combines histopathological examination with molecular genetic profiling, which requires days to weeks to achieve a precise and informative classification of CNS tumors. This study demonstrates the feasibility of rapid multiplex amplicon nanopore sequencing for identifying critical mutations relevant to molecular stratification of brain tumors within the timeframe of standard resection surgery. Utilizing live analysis of nanopore sequencing data, we evaluated the brain tumor-associated molecular markers IDH1 R132, IDH2 R172, <em>pTERT</em> C228 and C250, H3F3A K27 and G34, Hist1H3B K27, and BRAF V600. Our method achieved a turnaround time of 105 min at the point-of-care from receipt of a tumor biopsy to result with the potential to impact surgical strategy. Our approach can be integrated with recently developed DNA methylation-based diagnostic classification systems, corroborating diagnoses and even further specifying tumor grades, thus enabling a multimodal diagnostic intraoperative assessment of CNS malignancies.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"26 ","pages":"Pages 51-57"},"PeriodicalIF":4.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review and revamp of compositional data transformation: A new framework combining proportion conversion and contrast transformation","authors":"Yiqian Zhang ,&nbsp;Jonas Schluter ,&nbsp;Lijun Zhang ,&nbsp;Xuan Cao ,&nbsp;Robert R. Jenq ,&nbsp;Hao Feng ,&nbsp;Jonathan Haines ,&nbsp;Liangliang Zhang","doi":"10.1016/j.csbj.2024.11.003","DOIUrl":"10.1016/j.csbj.2024.11.003","url":null,"abstract":"<div><div>Due to the development of next-generation sequencing technology and an increased appreciation of their role in modulating host immunity and their potential as therapeutic agents, the human microbiome has emerged as a key area of interest in various biological investigations of human health and disease. However, microbiome data present a number of statistical challenges not addressed by existing methods, such as the varying sequencing depth, the compositionality, and zero inflation. Solutions like scaling and transformation methods help to mitigate heterogeneity and release constraints, but often introduce biases and yield inconsistent results on the same data. To address these issues, we conduct a systematic review of compositional data transformation, with a particular focus on the connection and distinction of existing techniques. Additionally, we create a new framework that enables the development of new transformations by combining proportion conversion with contrast transformations. This framework includes well-known methods such as Additive Log Ratio (ALR) and Centered Log Ratio (CLR) as special cases. Using this framework, we develop two novel transformations—Centered Arcsine Contrast (CAC) and Additive Arcsine Contrast (AAC)—which show enhanced performance in scenarios with high zero-inflation. Moreover, our findings suggest that ALR and CLR transformations are more effective when zero values are less prevalent. This comprehensive review and the innovative framework provide microbiome researchers with a significant direction to enhance data transformation procedures and improve analytical outcomes.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"23 ","pages":"Pages 4088-4107"},"PeriodicalIF":4.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Source-detector trajectory optimization for FOV extension in dental CBCT imaging","authors":"S M Ragib Shahriar Islam ,&nbsp;Ander Biguri ,&nbsp;Claudio Landi ,&nbsp;Giovanni Di Domenico ,&nbsp;Benedikt Schneider ,&nbsp;Pascal Grün ,&nbsp;Cristina Sarti ,&nbsp;Ramona Woitek ,&nbsp;Andrea Delmiglio ,&nbsp;Carola-Bibiane Schönlieb ,&nbsp;Dritan Turhani ,&nbsp;Gernot Kronreif ,&nbsp;Wolfgang Birkfellner ,&nbsp;Sepideh Hatamikia","doi":"10.1016/j.csbj.2024.11.010","DOIUrl":"10.1016/j.csbj.2024.11.010","url":null,"abstract":"<div><div>In dental imaging, Cone Beam Computed Tomography (CBCT) is a widely used imaging modality for diagnosis and treatment planning. Small dental scanning units are the most popular due to their cost-effectiveness. However, these small systems have the limitation of a small field of view (FOV) as the source and detector move at a limited angle in a circular path. This often limits the FOV size. In this study, we addressed this issue by modifying the source-detector trajectory of the small dental device. The main goal of this study was to extend the FOV algorithmically by acquiring projection data with optimal projection angulation and isocenter location rather than upgrading any physical parts of the device. A novel algorithm to implement a Volume of Interest (VOI) guided trajectory is developed in this study based on the small dental imaging device's geometry. In addition, this algorithm is fused with a previously developed off-axis scanning method which uses an elliptical trajectory, to compensate for the existing constraints and to further extend the FOV. A comparison with standard circular trajectory is performed. The FOV of such a standard trajectory is a circle of 11 cm diameter in the axial plane. The proposed novel trajectory extends the FOV significantly and a maximum FOV of 19.5 cm is achieved with the Structural Similarity Index Measure (SSIM) score ranging between (≈98-99%) in different VOIs. The study results indicate that the proposed source-detector trajectory can extend dental imaging FOV and increase imaging performance, which ultimately results in more precise diagnosis and enhanced patient outcomes.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"24 ","pages":"Pages 679-689"},"PeriodicalIF":4.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142655449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating population-based biobanks: Catalyst for advances in precision health","authors":"Jui-Chu Lin ,&nbsp;Yi-Lien Liu ,&nbsp;Wesley Wei-Wen Hsiao ,&nbsp;Chien-Te Fan","doi":"10.1016/j.csbj.2024.10.049","DOIUrl":"10.1016/j.csbj.2024.10.049","url":null,"abstract":"<div><div>Precision health extends beyond the scope of precision medicine and involves a broader range of activities, including the prediction, prevention, treatment, and management of diseases. Tailored to specific populations, precision health offers personalized treatment and preventive measures considering genetics, lifestyle behaviors, social determinants of health, and environmental factors. Precision medicine focuses on the personalized treatment of diseases, whereas precision health aims to promote health and prevent diseases using tools such as big data and advanced analytics to predict health risks and prevent diseases at the population level. Biobanks play a crucial role in achieving precision health because they provide well-characterized biological samples and related data for disease prediction, diagnosis, and treatment. Challenges in integrating different biobanks include data format consistency, privacy concerns, and legal constraints. Standardized methodologies and digitalization can mitigate these challenges. The integration of biobanks can facilitate comprehensive analyses across multiple datasets to achieve various research goals. This study proposes strategies to address these challenges, including the development of a dynamic consent mechanism for population-based biobanks using digitalization and blockchain technology. This study recommends the following: 1) integrating population-based biobanks, 2) introducing dynamic consent tools for human biobanks, and 3) using large human biobanks with dynamic consent for research on diverse diseases. These recommendations can increase the utility of biobanks in realizing precision health. A case study implemented at Taoyuan Tiansheng Hospital demonstrated the effectiveness of these recommendations for achieving precision health and enhancing the value of biobanks. Through a comprehensive examination of precision health and biobanks, this study provides valuable insights for researchers, healthcare professionals, and policymakers in the precision healthcare sector.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"24 ","pages":"Pages 690-698"},"PeriodicalIF":4.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142655450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BioPAX in 2024: Where we are and where we are heading","authors":"Cécile Beust ,&nbsp;Emmanuelle Becker ,&nbsp;Nathalie Théret ,&nbsp;Olivier Dameron","doi":"10.1016/j.csbj.2024.10.045","DOIUrl":"10.1016/j.csbj.2024.10.045","url":null,"abstract":"<div><div>In systems biology, the study of biological pathways plays a central role in understanding the complexity of biological systems. The massification of pathway data made available by numerous online databases in recent years has given rise to an important need for standardization of this data. The BioPAX format (Biological Pathway Exchange) emerged in 2010 as a solution for standardizing and exchanging pathway data across databases. BioPAX is a Semantic Web format associated to an ontology. It is highly expressive, allowing to finely describe biological pathways at the molecular and cellular levels, but the associated intrinsic complexity may be an obstacle to its widespread adoption.</div><div>Here, we report on the use of the BioPAX format in 2024. We compare how the different pathway databases use BioPAX to standardize their data and point out possible avenues for improvement to make full use of its potential. We also report on the various tools and software that have been developed to work with BioPAX data. Finally, we present a new concept of abstraction on BioPAX graphs that would allow to specifically target areas in a BioPAX graph needed for a specific analysis, thus differentiating the format suited for representation and the abstraction suited for contextual analysis.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"23 ","pages":"Pages 3999-4010"},"PeriodicalIF":4.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on federated learning in computational pathology","authors":"Lydia A. Schoenpflug ,&nbsp;Yao Nie ,&nbsp;Fahime Sheikhzadeh ,&nbsp;Viktor H. Koelzer","doi":"10.1016/j.csbj.2024.10.037","DOIUrl":"10.1016/j.csbj.2024.10.037","url":null,"abstract":"<div><div>Training generalizable computational pathology (CPATH) algorithms is heavily dependent on large-scale, multi-institutional data. Simultaneously, healthcare data underlies strict data privacy rules, hindering the creation of large datasets. Federated Learning (FL) is a paradigm addressing this dilemma, by allowing separate institutions to collaborate in a training process while keeping each institution's data private and exchanging model parameters instead. In this study, we identify and review key developments of FL for CPATH applications. We consider 15 studies, thereby evaluating the current status of exploring and adapting this emerging technology for CPATH applications. Proof-of-concept studies have been conducted across a wide range of CPATH use cases, showcasing the performance equivalency of models trained in a federated compared to a centralized manner. Six studies focus on model aggregation or model alignment methods reporting minor (<span><math><mn>0</mn><mo>∼</mo><mn>3</mn><mtext>%</mtext></math></span>) performance improvement compared to conventional FL techniques, while four studies explore domain alignment methods, resulting in more significant performance improvements (<span><math><mn>4</mn><mo>∼</mo><mn>20</mn><mtext>%</mtext></math></span>). To further reduce the privacy risk posed by sharing model parameters, four studies investigated the use of privacy preservation methods, where all methods demonstrated equivalent or slightly degraded performance (<span><math><mn>0.2</mn><mo>∼</mo><mn>6</mn><mtext>%</mtext></math></span> lower). To facilitate broader, real-world environment adoption, it is imperative to establish guidelines for the setup and deployment of FL infrastructure, alongside the promotion of standardized software frameworks. These steps are crucial to 1) further democratize CPATH research by allowing smaller institutions to pool data and computational resources 2) investigating rare diseases, 3) conducting multi-institutional studies, and 4) allowing rapid prototyping on private data.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"23 ","pages":"Pages 3938-3945"},"PeriodicalIF":4.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review on the state-of-the-art and research gaps regarding inorganic and carbon-based multicomponent and high-aspect ratio nanomaterials","authors":"Anastasios G. Papadiamantis ,&nbsp;Angelos Mavrogiorgis ,&nbsp;Stavros Papatzelos ,&nbsp;Dimitris Mintis ,&nbsp;Georgia Melagraki ,&nbsp;Iseult Lynch ,&nbsp;Antreas Afantitis","doi":"10.1016/j.csbj.2024.10.020","DOIUrl":"10.1016/j.csbj.2024.10.020","url":null,"abstract":"<div><div>This review explores the state-of-the-art with respect to multicomponent nanomaterials (MCNMs) and high aspect ratio nanomaterials (HARNs), with a focus on their physicochemical characterisation, applications, and hazard, fate, and risk assessment. Utilising the PRISMA approach, this study investigates specific MCNMs including cerium-zirconium mixtures (Ce_xZr_yO₂) and ZnO nanomaterials doped with transition metals and rare earth elements, as well as Titanium Carbide (TiC) nanomaterials contained in Ti-6Al-4V alloy powders. HARNs of interest include graphene, carbon-derived nanotubes (CNTs), and metallic nanowires, specifically Ag-based nanowires. The review reveals a significant shift in research and innovation (R&amp;I) efforts towards these advanced nanomaterials due to their unique properties and functionalities that promise enhanced performance across various applications including photocatalysis, antibacterial and biomedical uses, and advanced manufacturing. Despite the commercial potential of MCNMs and HARNs, the review identifies critical gaps in our understanding of their environmental fate and transformations upon exposure to new environments, and their potential adverse effects on organisms and the environment. The findings underscore the necessity for further research focused on the environmental transformations and toxicological profiles of these nanomaterials to inform Safe and Sustainable by Design (SSbD) strategies. This review contributes to the body of knowledge by cataloguing current research, identifying research gaps, and highlighting future directions for the development of MCNMs and HARNs, facilitating their safe and effective integration into industry.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"25 ","pages":"Pages 211-229"},"PeriodicalIF":4.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An AI-driven multiscale methodology to develop transparent wood as sustainable functional material by using the SSbD concept","authors":"Päivi Kivikytö-Reponen ,&nbsp;Stefania Fortino ,&nbsp;Veera Marttila ,&nbsp;Alexey Khakalo ,&nbsp;Kari Kolari ,&nbsp;Antti Puisto ,&nbsp;Daniele Nuvoli ,&nbsp;Alberto Mariani","doi":"10.1016/j.csbj.2024.10.022","DOIUrl":"10.1016/j.csbj.2024.10.022","url":null,"abstract":"<div><div>Efficient design, production, and optimization of new safe and sustainable by design materials for various industrial sectors is an on-going challenge for our society, poised to escalate in the future. Wood-based composite materials offer an attractive sustainable alternative to high impact materials such as glass and polymers and have been the focus of experimental research and development for years. Computational and AI-based materials design provides significant speed-up the development of these materials compared to traditional methods of development. However, reliable numerical models are essential for achieving this goal. The AI-TranspWood project, recently funded by the European Commission, has the ambition to develop such computational and AI-based tools in the context of transparent wood (TW), a promising composite with potential applications in various industrial fields. In this project we advance the development specifically by using an Artificial Intelligence (AI)-driven multiscale methodology.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"25 ","pages":"Pages 205-210"},"PeriodicalIF":4.4,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using patient-generated health data more efficient and effectively to facilitate the implementation of value-based healthcare in the EU – Innovation report","authors":"Frans Folkvord ,&nbsp;Jim Ingebretsen Carlson ,&nbsp;Manuel Ottaviano ,&nbsp;Diego Carvajal ,&nbsp;Liss Hernandez Gonzalez ,&nbsp;Rens van de Schoot ,&nbsp;Eva Turk ,&nbsp;Jordi Piera-Jiménez ,&nbsp;Caridad Pontes ,&nbsp;Marina Ramiro-Pareta ,&nbsp;Gerard Carot-Sans ,&nbsp;Eva Podovšovnik ,&nbsp;Vesna Levašič ,&nbsp;Kathrin Scheckenbach ,&nbsp;Martin Wagenmann ,&nbsp;Aron Szpisjak ,&nbsp;Bogi Eliasen ,&nbsp;Joe-Max Wakim ,&nbsp;Martin Ernst ,&nbsp;Yvonne Prinzellner ,&nbsp;Giuseppe Fico","doi":"10.1016/j.csbj.2024.10.026","DOIUrl":"10.1016/j.csbj.2024.10.026","url":null,"abstract":"<div><div>Healthcare services and products are rapidly changing due to the development of new technologies, offering relevant solutions to improve patient outcomes. Patient-Generated Health Data and knowledge-sharing across the European Union (EU) has a great potential of making healthcare provision more effective and efficient by putting the patient at the centre of the healthcare process. While such initiatives have been taken before, a uniting and overarching approach is still missing. The EU-funded IMPROVE project will develop an evidence-based and actual framework to effectively leverage the added value of people-centred integrated healthcare solutions, using predominantly PROMs, PPI, PREMs, and other Patient-Generated Health Data (PGHD). As a result, the project facilitates the effective and efficient implementation of Value-Based Healthcare across the EU by putting the patient central in the healthcare process.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"24 ","pages":"Pages 672-678"},"PeriodicalIF":4.4,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Easy-MODA: Simplifying standardised registration of scientific simulation workflows through MODA template guidelines powered by the Enalos Cloud Platform","authors":"Panagiotis D. Kolokathis ,&nbsp;Nikolaos K. Sidiropoulos ,&nbsp;Dimitrios Zouraris ,&nbsp;Dimitra-Danai Varsou ,&nbsp;Dimitris G. Mintis ,&nbsp;Andreas Tsoumanis ,&nbsp;Francesco Dondero ,&nbsp;Thomas E. Exner ,&nbsp;Haralambos Sarimveis ,&nbsp;Evgenia Chaideftou ,&nbsp;Martin Paparella ,&nbsp;Fotini Nikiforou ,&nbsp;Achilleas Karakoltzidis ,&nbsp;Spyros Karakitsios ,&nbsp;Dimosthenis Sarigiannis ,&nbsp;Jesper Friis ,&nbsp;Gerhard Goldbeck ,&nbsp;David A. Winkler ,&nbsp;Willie Peijnenburg ,&nbsp;Angela Serra ,&nbsp;Antreas Afantitis","doi":"10.1016/j.csbj.2024.10.018","DOIUrl":"10.1016/j.csbj.2024.10.018","url":null,"abstract":"<div><div>Modelling Data (MODA) reporting guidelines have been proposed for common terminology and for recording metadata for physics-based materials modelling and simulations in a CEN Workshop Agreement (CWA 17284:2018). Their purpose is similar to that of the Quantitative Structure-Activity Relationship (QSAR) model report form (QMRF) that aims to increase industry and regulatory confidence in QSAR models, but for a wider range of model types. Recently, the WorldFAIR project’s nanomaterials case study suggested that both QMRF and MODA templates are an important means to enhance compliance of nanoinformatics models, and their underpinning datasets, with the FAIR principles (Findable, Accessible, Interoperable, Reusable). Despite the advances in computational modelling of materials properties and phenomena, regulatory uptake of predictive models has been slow. This is, in part, due to concerns about lack of validation of complex models and lack of documentation of scientific simulations. The models are often complex, output can be hardware- and software-dependent, and there is a lack of shared standards. Despite advocating for standardised and transparent documentation of simulation protocols through its templates, the MODA guidelines are rarely used in practice by modellers because of a lack of tools for automating their creation, sharing, and storage. They also suffer from a paucity of user guidance on their use to document different types of models and systems. Such tools exist for the more well-established QMRF and have aided widespread implementation of QMRFs. To address this gap, a simplified procedure and online tool, Easy-MODA, has been developed to guide users through MODA creation for physics-based and data-based models, and their various combinations. Easy-MODA is available as a web-tool on the Enalos Cloud Platform (<span><span>https://www.enaloscloud.novamechanics.com/insight/moda/</span><svg><path></path></svg></span>). The tool streamlines the creation of detailed MODA documentation, even for complex multi-model workflows, and facilitates the registration of MODA workflows and documentation in a database, thereby increasing their Findability and thus Re-usability. This enhances communication, interoperability, and reproducibility in multiscale materials modelling and improves trust in the models through improved documentation. The use of the Easy-MODA tool is exemplified by a case study for nanotoxicity evaluation, involving interlinked models and data transformation, to demonstrate the effectiveness of the tool in integrating complex computational methodologies and its significant role in improving the FAIRness of scientific simulations.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"25 ","pages":"Pages 256-268"},"PeriodicalIF":4.4,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}