Biofilms research has evolved considerably in the last decade and is now generating large volumes of heterogeneous data. MIABiE, the international initiative on Biofilms, is devising guidelines for data interchange, and some databases provide access to biofilms experiments. However, the field is lacking appropriate bioinformatics tools in support of increasing operational and analytical needs. This paper presents a flexible and extensible open-source workbench for the operation and analysis of biofilms experiments, as follows: (i) the creation of customised experiments, (ii) the collection of various analytical results, following community standardisation guidelines and (iii) on-demand reporting and statistical evaluation

A. Jain

A.M. Sousa

B.M. Peters

D. Glez-Peña

K. Buckingham-Meyer

L. Hall-Stoodley

M.E. Davey

N.F. Azevedo

P.K. Sreenivasaiah

R.M. Donlan

U. Römling

Rodríguez, Gael Pérez

Glez-Peña, Daniel

Azevedo, N. F.

Pereira, Maria Olívia

Fdez-Riverola, Florentino

Lourenço, Anália

Universidade do Minho: RepositoriUM

BEW: Bioinformatics workbench for analysis of biofilms experimental data

 
J. Sáez-Rodríguez et al. (eds.), 8th International Conference on Practical Appl. of Comput.  
Biol. & Bioinform. (PACBB 2014), Advances in Intelligent Systems and Computing 294,  
49
DOI: 10.1007/978-3-319-07581-5_6, © Springer International Publishing Switzerland 2014 
 
BEW: Bioinformatics Workbench for Analysis  
of Biofilms Experimental Data 
Gael Pérez Rodríguez1, Daniel Glez-Peña1, Nuno F. Azevedo2, Maria Olívia Pereira3, 
Florentino Fdez-Riverola1, and Anália Lourenço1,2 
1 ESEI - Escuela Superior de Ingeniería Informática, Edificio Politécnico, Campus 
Universitario As Lagoas s/n, Universidad de Vigo, 32004 Ourense, Spain 
2 LEPABE – Dep. of Chemical Engineering, Faculty of Engineering, University of Porto,  
Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal 
3 IBB - Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, 
University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal 
gprodriguez2@esei.uvigo.es, {dgpena,riverola,analia}@uvigo.es, 
nazevedo@fe.up.pt, mopereira@deb.uminho.pt, analia@ceb.uminho.pt 
Abstract. Biofilms research has evolved considerably in the last decade and is 
now generating large volumes of heterogeneous data. MIABiE, the international 
initiative on Biofilms, is devising guidelines for data interchange, and some 
databases provide access to biofilms experiments. However, the field is lacking 
appropriate bioinformatics tools in support of increasing operational and 
analytical needs. This paper presents a flexible and extensible open-source 
workbench for the operation and analysis of biofilms experiments, as follows: 
(i) the creation of customised experiments, (ii) the collection of various 
analytical results, following community standardisation guidelines and (iii) on-
demand reporting and statistical evaluation. 
Keywords: Biofilms, standard operating procedures, data interchange, data 
analysis. 
1 Introduction 
Biofilms are surface-attached cellular agglomerates that are widespread in Nature and 
exhibit great abilities to adapt to environmental changes [1, 2]. Their actions can be 
seen as beneficial or detrimental to humans, depending on their ecological impact and 
our ability to act upon them [3, 4]. Notably, the resistance and resilience of biofilms 
attracts much attention from the biomedical research community due to the 
continuous emergence of multi-resistant strains in clinical settings, which are 
rendering conventional antibiotics ineffective [5, 6]. 
Biofilms research has witnessed a considerable development in the last decade. 
Conventional microbiological experimentation is giving place to large-scale 
multidisciplinary experimentation [7]. Cell viability, biomass formation, respiratory 
activity, morphological characterisation, and transcriptome and proteome profiling are 
just some examples of the methods of analysis now in use. Moreover, and due to the 
50 G.P. Rodríguez et al. 
 
diversity of settings where biofilms can be found, the environmental scenarios 
recreated in the lab can be quite different and sometimes challenging to implement. 
Repeatability, ruggedness and reproducibility tests are therefore conducted to ensure 
the quality of the acquired data and, in particular, the ability to compare results 
between laboratories [8, 9].  
The MIABiE initiative (http://miabie.org), encompassing an international body of 
Biofilms experts, is working on the definition of guidelines to document biofilms 
experiments and the standardisation of the nomenclature in use. Biofilms databases 
such as BiofOmics (http://biofomics.org) [10] and MorphoCol (http://morphocol.org) 
[11] are endorsing these guidelines and making experimental data freely available. 
However, the community is missing tools to take the best advantage of these 
resources, and it is notable the inexistence of bioinformatics tools dedicated to 
biofilms data operation and analysis. In particular, unstructured data operation, using 
Excel or similar tools, compromises data standardisation and thus, any form of 
computer-aided processing and analysis.  
This paper presents the first software tool dedicated to Biofilms: the Biofilms  
Experiment Workbench (BEW). The primary aim is to cover for primary intra-
laboratory data collection and analysis necessities. Previous work on data 
standardisation and computerised data structuring [11], now complemented by 
MIABiE guidelines, established the starting point of development. A specialised 
markup language is defined now as grounds to document experiments, and to 
effectively promote data interchange across resources and software tools. Moreover, 
the application is developed with AIBench, an open-source Java desktop application 
framework [14], to ensure a flexible, cross-platform and interoperable development 
suitable to sustain future interactions with other Biofilms-related tools. 
The next sections detail the markup language as well as the design and main  
functionalities of BEW.  
2 Biofilms Markup Language 
The current inability to exchange experiments between laboratories has its roots in the 
lack of a common format for describing Biofilms experiments. The modelling of 
Biofilm experiments is challenged by the complexity and variability of the studies. 
Studies may vary widely in aspects as important as: the conditions tested (related to 
the goals of analysis), the microorganisms studied (with implicit growth and other 
biological specifics), the methods of analysis used (data is only comparable for 
similar methods), specific data pre-processing (e.g. the calculation of dilution rates or 
log reductions), and the number of replicates and reproductions performed to ensure 
the validity of the study. 
These issues were discussed with field experts - at the Eurobiofilms 2013 meeting in 
Ghent, Belgium (9-12 September 2013) - as means to accommodate for as much of this 
complexity and variability as possible, and anticipate new requirements resulting from 
the increasing use of high-throughput methods. Then, XML, the eXtensible Markup 
Language [12], was elected to formalise the data structure because of its portability and 
widespread acceptance as a standard data language for Bioinformatics [13]. 
 BEW: Bioinformatics 
 
At the end, we came by
experiment that considers fo
• identification an
authors of the
experiment, and
• method of analy
of resulting data
• condition, i.e. 
analysis (e.g. a 
• data series that 
given set of con
The definition of an exp
these various components (F
Fig. 1. Skeleton of the definiti
top-level elements 
3 BEW: The Biofi
BEW is a desktop-based ap
data resulting from Biofilms
an open-source Java desktop
in the domain of translat
incorporates a plug-in for the
the libraries JFreeChart for 
and write Excel sheets (http
 
Workbench for Analysis of Biofilms Experimental Data 
 a very generic skeleton for the description of a biof
ur major conceptual elements:  
d authorship, including the name of the institution and 
 experiment, the title and a short description of 
 any associated publications;  
sis, which comprises a set of test conditions and a num
 series;  
a experimental condition tested by a given method
value of temperature or a dose of an antimicrobial agent
describe the data obtained by a method of analysis fo
ditions.  
eriment in XML simply consists of lists of one or more
ig. 1). 
 
on of a biofilm experiment in XML format, showing all poss
lms Workbench 
plication dedicated to the management and analysis of 
 experiments. The application was developed with AIBen
 application framework for scientific software developm
ional biomedicine [14]. As illustrated in Fig. 2, BE
 R statistical computing tool (http://www.r-project.org/) 
data plotting (http://www.jfree.org/jfreechart/), JXL to r
://jexcelapi.sourceforge.net/), and JSoup for working w
51 
ilm 
the 
the 
ber 
 of 
);  
r a 
 of 
ible 
the 
ch, 
ent 
W 
and 
ead 
ith  
52 G.P. Rodríguez et al
 
HTML documents (http://jso
and data analysis operatio
regarding statistical analysi
Fig. 2. General
The next subsections de
currently provided by the so
3.1 Experiment Manag
In accordance to standard
supports both .xml and .xls 
(as described in section 2) a
experiments from/to the sta
The experiment should 
community-wide unambigu
terms of authorship (autho
publications. Then, the ex
overall settings or constan
methods of analysis. Given
user interface was made as 
of variable nature and ex
standardisation and systema
to detach the user from unn
3.2 Statistical Analysis 
BEW is equipped with a 
construction of data plots as
Plots and statistical te
references of expected fun
enable the use of a wider r
BEW analytical componen
while the R plug-in grants a
AIBench
Core
Workbench
Plugins
. 
up.org/). These third-parties support main data process
ns whilst enable future adaptation or extension (nota
s). 
 
 architecture of the software components in BEW 
scribe the core management and analysis functionali
ftware. 
ement 
isation guidelines and to cope with data legacy, BE
data representation formats. The XML is the native form
nd wrapping functionalities are provided to import/exp
ndardised and hierarchy-based Excel format [11]. 
be comprehensively described in order to guarantee
ous interpretation. First, the experiment is “identified”
r and institution), author’s summary and any associa
perimental setup is detailed and, more specifically, 
t conditions, and the conditions tested by each of 
 the wide range of analyses now conducted for biofil
flexible and intuitive as possible to enable the construct
tent data “worksheets” (Fig. 3). In particular, metad
tic data structuring were encapsulated in logical selecti
ecessary computational details.  
powerful analytical component that supports on-dem
 well as statistical data testing.  
sts usually present in Biofilms publications served
ctionalities, but the component was developed such
ange of plots and tests. Two free third-party tools supp
t: the JFreeChart library provides for plotting abili
ccess to broad statistical analysis.  
BEW
Core
RPlugin
Libraries
JFreeChart JXL JSoup
ing 
bly 
ties 
W 
at 
ort 
 its 
 in 
ted 
the 
the 
ms, 
ion 
ata 
ons 
and 
 as 
 to 
ort 
ties 
 BEW: Bioinformatics 
 
Fig. 3. Snapsh
Data plotting was mad
visualisation of the results 
(Fig. 4).  
Fig. 4. Snapshot of
Likewise, BEW has no p
decides which tests shoul
heterogeneity of existing e
testing usually aims to anal
therapeutic conditions (Fig
Workbench for Analysis of Biofilms Experimental Data 
 
ot of the description of an experimental analysis 
e as flexible as possible in order to accommodate 
produced by virtually any combination of test conditi
 
 a plot representing the test results for three conditions 
re-established pipeline for statistical analysis, i.e. the u
d be executed for his data. This is crucial given 
xperimentation. For example, antimicrobial susceptibi
yse the variance of results obtained under different sets
. 5). In turn, repeatability and reproducibility experime
53 
the 
ons 
ser 
the 
lity 
 of 
nts 
54 G.P. Rodríguez et al
 
are quite unique in the goal
results. Typically, research
tests, which are not used in 
Fig. 5. Snap
3.3 Reports 
Report capabilities are use
describe the experiment in t
as to provide a summary of 
This functionality is me
when depositing an experi
peer-review. It serves the 
actual inspection of results
visualise the experiments in
4 Conclusions 
In this paper we present B
Biofilms experiments. It is
and analysis requirements o
XML-based markup langua
Widespread use of Biofi
will benefit users as well as
common format for public
systematic experiment comp
. 
 of analysis – standard operation – and the interpretation
ers are interested in conducting ANOVA Gauge R
most of the other experiments. 
shot of the execution of an analysis of variance 
ful to automatically document the experiment, notably
erms of methods of analysis and tested conditions, as w
the resulting data (Fig. 6).  
ant to complement the XML file, being of practical 
ment in a public database or submitting a manuscrip
purpose of introducing the work developed, prior to 
 by means of the XML file. Also, it can be used to p
 Web resources and tools.  
EW, a desktop application devoted to the managemen
 the very first tool developed to meet the data process
f the Biofilms domain. As such, its first contribution 
ge for the general description of biofilm experiments.  
lms markup language in resources and software packa
 developers. With greater interaction between tools, an
ations and databases, researchers will be able to perfo
arison and data interchange.  
 of 
&R 
 
 to 
ell 
use 
t to 
the 
re-
t of 
ing 
is a 
ges 
d a 
rm 
 BEW: Bioinformatics 
 
Fig. 6. S
Moreover, BEW archite
anticipation of the various r
of these experiments and th
researcher’s daily operation
necessary statistical discuss
laboratory frontiers, notabl
experimental data in comm
laboratory experiment comp
Workbench for Analysis of Biofilms Experimental Data 
napshot of the Web report of an experiment 
cture is designed to be flexible and easily extensible
equirements emerging from the growing multidisciplin
e diverse nature of studies. At first, BEW aims to supp
, both in dealing with the generated data and executing 
ion. In a near future, BEW is expected to go beyond in
y by enabling the automatic deposition of standardi
unity databases, such as BiofOmics, and enabling in
arisons.  
55 
 
 
, in 
ary 
ort 
the 
tra-
sed 
ter-
56 G.P. Rodríguez et al. 
 
Acknowledgements. This work was supported by the [INOU13-07] project from the 
University of Vigo, the IBB-CEB, the Fundação para a Ciência e Tecnologia (FCT) 
and the European Community fund FEDER, through Program COMPETE [FCT 
Project number PTDC/SAU-SAP/113196/2009/FCOMP-01-0124-FEDER-016012], 
and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer 
Europa (2012/273). The research leading to these results has received funding from 
the European Union's Seventh Framework Programme FP7/REGPOT-2012-2013.1 
under grant agreement n° 316265, BIOCAPS. This document reflects only the 
author’s views and the European Union is not liable for any use that may be made of 
the information contained herein. 
References 
1. Hall-Stoodley, L., Costerton, J.W., Stoodley, P.: Bacterial biofilms: from the natural 
environment to infectious diseases. Nat. Rev. Microbiol. 2, 95–108 (2004) 
2. Donlan, R.M.: Biofilms: microbial life on surfaces. Emerg. Infect. Dis. 8, 881–890 (2002) 
3. Davey, M.E., O’toole, G.A.: Microbial biofilms: from ecology to molecular genetics. 
Microbiol. Mol. Biol. Rev. 64, 847–867 (2000) 
4. Jain, A., Gupta, Y., Agrawal, R., Khare, P., Jain, S.K.: Biofilms–a microbial life 
perspective: a critical review. Crit. Rev. Ther. Drug Carrier Syst. 24, 393–443 (2007) 
5. Römling, U., Balsalobre, C.: Biofilm infections, their resilience to therapy and innovative 
treatment strategies. J. Intern. Med. 272, 541–561 (2012) 
6. Peters, B.M., Jabra-Rizk, M.A., O’May, G.A., Costerton, J.W., Shirtliff, M.E.: 
Polymicrobial interactions: impact on pathogenesis and human disease. Clin. Microbiol. 
Rev. 25, 193–213 (2012) 
7. Azevedo, N.F., Lopes, S.P., Keevil, C.W., Pereira, M.O., Vieira, M.J.: Time to “go large” on 
biofilm research: advantages of an omics approach. Biotechnol. Lett. 31, 477–485 (2009) 
8. Buckingham-Meyer, K., Goeres, D.M., Hamilton, M.A.: Comparative evaluation of 
biofilm disinfectant efficacy tests. J. Microbiol. Methods 70, 236–244 (2007) 
9. Hamilton, M.A.: KSA-SM-03 - Desirable attributes of a standardized method. Stand. 
METHODS Test. Surf. Disinfect (2010) 
10. Lourenço, A., Ferreira, A., Veiga, N., Machado, I., Pereira, M.O., Azevedo, N.F.: 
BiofOmics: A Web Platform for the Systematic and Standardized Collection of High-
Throughput Biofilm Data. PLoS One 7, e39960 (2012) 
11. Sousa, A.M., Ferreira, A., Azevedo, N.F., Pereira, M.O., Lourenço, A.: Computational 
approaches to standard-compliant biofilm data for reliable analysis and integration. J. 
Integr. Bioinform. 9, 203 (2012) 
12. Bray, T., Paoli, J., Sperberg-McQueen, C.M.: Extensible markup language, XML (1998),  
http://www.w3.org/TR/1998/REC-xml-19980210 
13. Sreenivasaiah, P.K., Kim, D.H.: Current trends and new challenges of databases and web 
applications for systems driven biological research. Front. Physiol. 1, 147 (2010) 
14. Glez-Peña, D., Reboiro-Jato, M., Maia, P., Rocha, M., Díaz, F., Fdez-Riverola, F.: 
AIBench: a rapid application development framework for translational research in 
biomedicine. Comput. Methods Programs Biomed. 98, 191–203 (2010) 


English

Gael Pérez Rodríguez

Daniel Glez-Peña

Nuno F. Azevedo

Maria Olívia Pereira

Florentino Fdez-Riverola

Anália Lourenço

Crossref

BEW: Bioinformatics Workbench for Analysis of Biofilms Experimental Data

 J. Sáez-Rodríguez et al. (eds.), 8th International Conference on Practical Appl. of Comput.  Biol. & Bioinform. (PACBB 2014), Advances in Intelligent Systems and Computing 294,  49DOI: 10.1007/978-3-319-07581-5_6, © Springer International Publishing Switzerland 2014  BEW: Bioinformatics Workbench for Analysis  of Biofilms Experimental Data Gael Pérez Rodríguez1, Daniel Glez-Peña1, Nuno F. Azevedo2, Maria Olívia Pereira3, Florentino Fdez-Riverola1, and Anália Lourenço1,2 1 ESEI - Escuela Superior de Ingeniería Informática, Edificio Politécnico, Campus Universitario As Lagoas s/n, Universidad de Vigo, 32004 Ourense, Spain 2 LEPABE – Dep. of Chemical Engineering, Faculty of Engineering, University of Porto,  Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal 3 IBB - Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal gprodriguez2@esei.uvigo.es, {dgpena,riverola,analia}@uvigo.es, nazevedo@fe.up.pt, mopereira@deb.uminho.pt, analia@ceb.uminho.pt Abstract. Biofilms research has evolved considerably in the last decade and is now generating large volumes of heterogeneous data. MIABiE, the international initiative on Biofilms, is devising guidelines for data interchange, and some databases provide access to biofilms experiments. However, the field is lacking appropriate bioinformatics tools in support of increasing operational and analytical needs. This paper presents a flexible and extensible open-source workbench for the operation and analysis of biofilms experiments, as follows: (i) the creation of customised experiments, (ii) the collection of various analytical results, following community standardisation guidelines and (iii) on-demand reporting and statistical evaluation. Keywords: Biofilms, standard operating procedures, data interchange, data analysis. 1 Introduction Biofilms are surface-attached cellular agglomerates that are widespread in Nature and exhibit great abilities to adapt to environmental changes [1, 2]. Their actions can be seen as beneficial or detrimental to humans, depending on their ecological impact and our ability to act upon them [3, 4]. Notably, the resistance and resilience of biofilms attracts much attention from the biomedical research community due to the continuous emergence of multi-resistant strains in clinical settings, which are rendering conventional antibiotics ineffective [5, 6]. Biofilms research has witnessed a considerable development in the last decade. Conventional microbiological experimentation is giving place to large-scale multidisciplinary experimentation [7]. Cell viability, biomass formation, respiratory activity, morphological characterisation, and transcriptome and proteome profiling are just some examples of the methods of analysis now in use. Moreover, and due to the 50 G.P. Rodríguez et al.  diversity of settings where biofilms can be found, the environmental scenarios recreated in the lab can be quite different and sometimes challenging to implement. Repeatability, ruggedness and reproducibility tests are therefore conducted to ensure the quality of the acquired data and, in particular, the ability to compare results between laboratories [8, 9].  The MIABiE initiative (http://miabie.org), encompassing an international body of Biofilms experts, is working on the definition of guidelines to document biofilms experiments and the standardisation of the nomenclature in use. Biofilms databases such as BiofOmics (http://biofomics.org) [10] and MorphoCol (http://morphocol.org) [11] are endorsing these guidelines and making experimental data freely available. However, the community is missing tools to take the best advantage of these resources, and it is notable the inexistence of bioinformatics tools dedicated to biofilms data operation and analysis. In particular, unstructured data operation, using Excel or similar tools, compromises data standardisation and thus, any form of computer-aided processing and analysis.  This paper presents the first software tool dedicated to Biofilms: the Biofilms  Experiment Workbench (BEW). The primary aim is to cover for primary intra-laboratory data collection and analysis necessities. Previous work on data standardisation and computerised data structuring [11], now complemented by MIABiE guidelines, established the starting point of development. A specialised markup language is defined now as grounds to document experiments, and to effectively promote data interchange across resources and software tools. Moreover, the application is developed with AIBench, an open-source Java desktop application framework [14], to ensure a flexible, cross-platform and interoperable development suitable to sustain future interactions with other Biofilms-related tools. The next sections detail the markup language as well as the design and main  functionalities of BEW.  2 Biofilms Markup Language The current inability to exchange experiments between laboratories has its roots in the lack of a common format for describing Biofilms experiments. The modelling of Biofilm experiments is challenged by the complexity and variability of the studies. Studies may vary widely in aspects as important as: the conditions tested (related to the goals of analysis), the microorganisms studied (with implicit growth and other biological specifics), the methods of analysis used (data is only comparable for similar methods), specific data pre-processing (e.g. the calculation of dilution rates or log reductions), and the number of replicates and reproductions performed to ensure the validity of the study. These issues were discussed with field experts - at the Eurobiofilms 2013 meeting in Ghent, Belgium (9-12 September 2013) - as means to accommodate for as much of this complexity and variability as possible, and anticipate new requirements resulting from the increasing use of high-throughput methods. Then, XML, the eXtensible Markup Language [12], was elected to formalise the data structure because of its portability and widespread acceptance as a standard data language for Bioinformatics [13].  BEW: Bioinformatics  At the end, we came byexperiment that considers fo• identification anauthors of theexperiment, and• method of analyof resulting data• condition, i.e. analysis (e.g. a • data series that given set of conThe definition of an expthese various components (FFig. 1. Skeleton of the definititop-level elements 3 BEW: The BiofiBEW is a desktop-based apdata resulting from Biofilmsan open-source Java desktopin the domain of translatincorporates a plug-in for thethe libraries JFreeChart for and write Excel sheets (http Workbench for Analysis of Biofilms Experimental Data  a very generic skeleton for the description of a biofur major conceptual elements:  d authorship, including the name of the institution and  experiment, the title and a short description of  any associated publications;  sis, which comprises a set of test conditions and a num series;  a experimental condition tested by a given methodvalue of temperature or a dose of an antimicrobial agentdescribe the data obtained by a method of analysis foditions.  eriment in XML simply consists of lists of one or moreig. 1).  on of a biofilm experiment in XML format, showing all posslms Workbench plication dedicated to the management and analysis of  experiments. The application was developed with AIBen application framework for scientific software developmional biomedicine [14]. As illustrated in Fig. 2, BE R statistical computing tool (http://www.r-project.org/) data plotting (http://www.jfree.org/jfreechart/), JXL to r://jexcelapi.sourceforge.net/), and JSoup for working w51 ilm the the ber  of );  r a  of ible the ch, ent W and ead ith  52 G.P. Rodríguez et al HTML documents (http://jsoand data analysis operatioregarding statistical analysiFig. 2. GeneralThe next subsections decurrently provided by the so3.1 Experiment ManagIn accordance to standardsupports both .xml and .xls (as described in section 2) aexperiments from/to the staThe experiment should community-wide unambiguterms of authorship (authopublications. Then, the exoverall settings or constanmethods of analysis. Givenuser interface was made as of variable nature and exstandardisation and systemato detach the user from unn3.2 Statistical Analysis BEW is equipped with a construction of data plots asPlots and statistical tereferences of expected funenable the use of a wider rBEW analytical componenwhile the R plug-in grants aAIBenchCoreWorkbenchPlugins. up.org/). These third-parties support main data processns whilst enable future adaptation or extension (notas).   architecture of the software components in BEW scribe the core management and analysis functionaliftware. ement isation guidelines and to cope with data legacy, BEdata representation formats. The XML is the native formnd wrapping functionalities are provided to import/expndardised and hierarchy-based Excel format [11]. be comprehensively described in order to guaranteeous interpretation. First, the experiment is “identified”r and institution), author’s summary and any associaperimental setup is detailed and, more specifically, t conditions, and the conditions tested by each of  the wide range of analyses now conducted for biofilflexible and intuitive as possible to enable the constructtent data “worksheets” (Fig. 3). In particular, metadtic data structuring were encapsulated in logical selectiecessary computational details.  powerful analytical component that supports on-dem well as statistical data testing.  sts usually present in Biofilms publications servedctionalities, but the component was developed suchange of plots and tests. Two free third-party tools suppt: the JFreeChart library provides for plotting abiliccess to broad statistical analysis.  BEWCoreRPluginLibrariesJFreeChart JXL JSouping bly ties W at ort  its  in ted the the ms, ion ata ons and  as  to ort ties  BEW: Bioinformatics  Fig. 3. SnapshData plotting was madvisualisation of the results (Fig. 4).  Fig. 4. Snapshot ofLikewise, BEW has no pdecides which tests shoulheterogeneity of existing etesting usually aims to analtherapeutic conditions (FigWorkbench for Analysis of Biofilms Experimental Data  ot of the description of an experimental analysis e as flexible as possible in order to accommodate produced by virtually any combination of test conditi  a plot representing the test results for three conditions re-established pipeline for statistical analysis, i.e. the ud be executed for his data. This is crucial given xperimentation. For example, antimicrobial susceptibiyse the variance of results obtained under different sets. 5). In turn, repeatability and reproducibility experime53 the ons ser the lity  of nts 54 G.P. Rodríguez et al are quite unique in the goalresults. Typically, researchtests, which are not used in Fig. 5. Snap3.3 Reports Report capabilities are usedescribe the experiment in tas to provide a summary of This functionality is mewhen depositing an experipeer-review. It serves the actual inspection of resultsvisualise the experiments in4 Conclusions In this paper we present BBiofilms experiments. It isand analysis requirements oXML-based markup languaWidespread use of Biofiwill benefit users as well ascommon format for publicsystematic experiment comp.  of analysis – standard operation – and the interpretationers are interested in conducting ANOVA Gauge Rmost of the other experiments. shot of the execution of an analysis of variance ful to automatically document the experiment, notablyerms of methods of analysis and tested conditions, as wthe resulting data (Fig. 6).  ant to complement the XML file, being of practical ment in a public database or submitting a manuscrippurpose of introducing the work developed, prior to  by means of the XML file. Also, it can be used to p Web resources and tools.  EW, a desktop application devoted to the managemen the very first tool developed to meet the data processf the Biofilms domain. As such, its first contribution ge for the general description of biofilm experiments.  lms markup language in resources and software packa developers. With greater interaction between tools, anations and databases, researchers will be able to perfoarison and data interchange.   of &R   to ell use t to the re-t of ing is a ges d a rm  BEW: Bioinformatics  Fig. 6. SMoreover, BEW architeanticipation of the various rof these experiments and thresearcher’s daily operationnecessary statistical discusslaboratory frontiers, notablexperimental data in commlaboratory experiment compWorkbench for Analysis of Biofilms Experimental Data napshot of the Web report of an experiment cture is designed to be flexible and easily extensibleequirements emerging from the growing multidiscipline diverse nature of studies. At first, BEW aims to supp, both in dealing with the generated data and executing ion. In a near future, BEW is expected to go beyond iny by enabling the automatic deposition of standardiunity databases, such as BiofOmics, and enabling inarisons.  55   , in ary ort the tra-sed ter-56 G.P. Rodríguez et al.  Acknowledgements. This work was supported by the [INOU13-07] project from the University of Vigo, the IBB-CEB, the Fundação para a Ciência e Tecnologia (FCT) and the European Community fund FEDER, through Program COMPETE [FCT Project number PTDC/SAU-SAP/113196/2009/FCOMP-01-0124-FEDER-016012], and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273). The research leading to these results has received funding from the European Union's Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n° 316265, BIOCAPS. This document reflects only the author’s views and the European Union is not liable for any use that may be made of the information contained herein. References 1. Hall-Stoodley, L., Costerton, J.W., Stoodley, P.: Bacterial biofilms: from the natural environment to infectious diseases. Nat. Rev. Microbiol. 2, 95–108 (2004) 2. Donlan, R.M.: Biofilms: microbial life on surfaces. Emerg. Infect. Dis. 8, 881–890 (2002) 3. Davey, M.E., O’toole, G.A.: Microbial biofilms: from ecology to molecular genetics. Microbiol. Mol. Biol. Rev. 64, 847–867 (2000) 4. Jain, A., Gupta, Y., Agrawal, R., Khare, P., Jain, S.K.: Biofilms–a microbial life perspective: a critical review. Crit. Rev. Ther. Drug Carrier Syst. 24, 393–443 (2007) 5. Römling, U., Balsalobre, C.: Biofilm infections, their resilience to therapy and innovative treatment strategies. J. Intern. Med. 272, 541–561 (2012) 6. Peters, B.M., Jabra-Rizk, M.A., O’May, G.A., Costerton, J.W., Shirtliff, M.E.: Polymicrobial interactions: impact on pathogenesis and human disease. Clin. Microbiol. Rev. 25, 193–213 (2012) 7. Azevedo, N.F., Lopes, S.P., Keevil, C.W., Pereira, M.O., Vieira, M.J.: Time to “go large” on biofilm research: advantages of an omics approach. Biotechnol. Lett. 31, 477–485 (2009) 8. Buckingham-Meyer, K., Goeres, D.M., Hamilton, M.A.: Comparative evaluation of biofilm disinfectant efficacy tests. J. Microbiol. Methods 70, 236–244 (2007) 9. Hamilton, M.A.: KSA-SM-03 - Desirable attributes of a standardized method. Stand. METHODS Test. Surf. Disinfect (2010) 10. Lourenço, A., Ferreira, A., Veiga, N., Machado, I., Pereira, M.O., Azevedo, N.F.: BiofOmics: A Web Platform for the Systematic and Standardized Collection of High-Throughput Biofilm Data. PLoS One 7, e39960 (2012) 11. Sousa, A.M., Ferreira, A., Azevedo, N.F., Pereira, M.O., Lourenço, A.: Computational approaches to standard-compliant biofilm data for reliable analysis and integration. J. Integr. Bioinform. 9, 203 (2012) 12. Bray, T., Paoli, J., Sperberg-McQueen, C.M.: Extensible markup language, XML (1998),  http://www.w3.org/TR/1998/REC-xml-19980210 13. Sreenivasaiah, P.K., Kim, D.H.: Current trends and new challenges of databases and web applications for systems driven biological research. Front. Physiol. 1, 147 (2010) 14. Glez-Peña, D., Reboiro-Jato, M., Maia, P., Rocha, M., Díaz, F., Fdez-Riverola, F.: AIBench: a rapid application development framework for translational research in biomedicine. Comput. Methods Programs Biomed. 98, 191–203 (2010) 

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BEW: Bioinformatics workbench for analysis of biofilms experimental data

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