Enabling systematic, harmonised and large-scale biofilms data computation: The Biofilms Experiment Workbench

Pérez-Rodríguez, Gael; Glez-Peña, Daniel; Azevedo, Nuno F.; Fdez-Riverola, Florentino; Lourenço, Anália

doi:10.1016/j.cmpb.2014.12.005

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…BEW is the first software tool dedicated to biofilms data operation and analysis (Perez-Rodriguez et al, 2015). It supports structured and standardized documentation of experiments, statistical assessment of various analytical results, on-demand and Web-publishable experiment reporting, experiment publication/ retrieval in/from public databases, and comparison of results between laboratories.…”

Section: Computerized Data Operation and Analysismentioning

confidence: 99%

Critical review on biofilm methods

Azeredo

Azevedo

Briandet

et al. 2016

Critical Reviews in Microbiology

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679

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Biofilms are widespread in nature and constitute an important strategy implemented by microorganisms to survive in sometimes harsh environmental conditions. They can be beneficial or have a negative impact particularly when formed in industrial settings or on medical devices. As such, research into the formation and elimination of biofilms is important for many disciplines. Several new methodologies have been recently developed for, or adapted to, biofilm studies that have contributed to deeper knowledge on biofilm physiology, structure and composition. In this review, traditional and cutting-edge methods to study biofilm biomass, viability, structure, composition and physiology are addressed. Moreover, as there is a lack of consensus among the diversity of techniques used to grow and study biofilms. This review intends to remedy this, by giving a critical perspective, highlighting the advantages and limitations of several methods. Accordingly, this review aims at helping scientists in finding the most appropriate and up-to-date methods to study their biofilms. ARTICLE HISTORY

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Section: Computerized Data Operation and Analysismentioning

confidence: 99%

Critical review on biofilm methods

Azeredo

Azevedo

Briandet

et al. 2016

Critical Reviews in Microbiology

Self Cite

784

679

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“…Moreover, databases such as BiofOmics (http://biofo mics. org) and Biofilms Experiment Workbench (BEW) (http:// sing.ei.uvigo.es/bew) offers public web access to biofilm studies and enables full management and analysis of experiments and inter-lab experiments (Lourenço, Rego, et al, 2012;Perez-Rodriguez et al, 2015). However, the wider applications of these novel technologies and data informatics in food related biofilm research need to be further explored in future.…”

Section: Detection Of Biofilmsmentioning

confidence: 99%

Biofilms as a microbial hazard in the food industry: A scoping review

Sharan

Vijay

Dhaka

et al. 2022

Journal of Applied Microbiology

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Biofilms pose a serious public health hazard with a significant economic impact on the food industry. The present scoping review is designed to analyse the literature published during 2001–2020 on biofilm formation of microbes, their detection methods, and association with antimicrobial resistance (if any). The peer‐reviewed articles retrieved from 04 electronic databases were assessed using PRISMA‐ScR guidelines. From the 978 preliminary search results, a total of 88 publications were included in the study. On analysis, the commonly isolated pathogens were Listeria monocytogenes, Staphylococcus aureus, Salmonella spp., Escherichia coli, Bacillus spp., Vibrio spp., Campylobacter jejuni and Clostridium perfringens. The biofilm‐forming ability of microbes was found to be influenced by various factors such as attachment surfaces, temperature, presence of other species, nutrient availability etc. A total of 18 studies characterized the biofilm‐forming genes, particularly for S. aureus, Salmonella spp., and E. coli. In most studies, polystyrene plate and/or stainless‐steel coupons were used for biofilm formation, and the detection was carried out by crystal violet assays and/or by plate counting method. The strain‐specific significant differences in biofilm formation were observed in many studies, and few studies carried out analysis of multi‐species biofilms. The association between biofilm formation and antimicrobial resistance was not clearly defined. Further, viable but non‐culturable form of the foodborne pathogens is posing an unseen (by conventional cultivation techniques) but potent threat to the food safety. The present review recommends the need for carrying out systematic surveys and risk analysis of biofilms in food chain to highlight the evidence‐based public health concerns, especially in regions where microbiological food hazards are quite prevalent.

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“…The DEWE software v1.2 is implemented in Java 8 using AIBench [32], which is a framework for the rapid development of scientific applications, with several successful biomedical developments [33][34][35][36]. The source code of DEWE is divided into four modules: (i) the api, which contains the Application Programming Interface (API) definition; (ii) the core, which incorporates the default API implementation; (iii) the gui, which includes several reusable GUI components; and, (iv) the aibench, which implements the final GUI application.…”

Section: Dewe Implementationmentioning

confidence: 99%

DEWE: A novel tool for executing differential expression RNA-Seq workflows in biomedical research

López-Fernández

Blanco-Míguez

Fdez-Riverola

et al. 2019

Computers in Biology and Medicine

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Background: Transcriptomics profiling aims to identify and quantify all transcripts present within a cell type or tissue at a particular state, and thus provide information on the genes expressed in specific experimental settings, differentiation or disease conditions. RNA-Seq technology is becoming the standard approach for such studies, but available analysis tools are often hard to install, configure and use by users without advanced bioinformatics skills. Methods: Within reason, DEWE aims to make RNA-Seq analysis as easy for non-proficient users as for experienced bioinformaticians. DEWE supports two well-established and widely used differential expression analysis workflows: using Bowtie2 or HISAT2 for sequence alignment; and, both applying StringTie for quantification, and Ballgown and edgeR for differential expression analysis. Also, it enables the tailored execution of individual tools as well as helps with the management and visualisation of differential expression results. Results: DEWE provides a user-friendly interface designed to reduce the learning curve of less knowledgeable users while enabling analysis customisation and software extension by advanced users. Docker technology helps overcome installation and configuration hurdles. In addition, DEWE produces high quality and publication-ready outputs in the form of tab-delimited files and figures, as well as helps researchers with further analyses, such as pathway enrichment analysis. Conclusions: The abilities of DEWE are exemplified here by practical application to a comparative analysis of monocytes and monocyte-derived dendritic cells, a study of clinical relevance. DEWE installers and documentation are freely available at https://www.sing-group.org/dewe.

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Enabling systematic, harmonised and large-scale biofilms data computation: The Biofilms Experiment Workbench

Abstract: Background and objective: Biofilms are receiving increasing attention from the

Cited by 8 publications

References 22 publications

Critical review on biofilm methods

Critical review on biofilm methods

Biofilms as a microbial hazard in the food industry: A scoping review

DEWE: A novel tool for executing differential expression RNA-Seq workflows in biomedical research

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