PROTOFILWWA computational platform for the analysis of the relationships between
microorganisms and environmental parameters in activated sludge plants
José Fernandes
Bioinformatics Master Thesis
Prof. Anália Lourenço
Prof. Ana Nicolau
System requirements
• Insertion and retrieval of data has to be done quickly and easily
• Should be possible to export the data so it can be analyzed with other informatics
systems
• Should support statistical assessments
• Have user-friendly visualization capabilities
• Controlled access to data, based on user roles, accounting for data privacy issues
• Easy dissemination of related studies and results
• Always online (web-based)
• Help finding additional information about the microorganisms present in the biological
samples
Overview of the workflow of field and lab work
PROTOFILWWPROTOFILWW
1.635 lines x 137 columns
ProtoFilWW system major components
1. Content Management component: supports the
researchers managing and analyzing the data obtained
from the WWTP’s samples
2. Text Mining component: finding additional information
about the microorganisms present in the biological
samples
High-level integration perspective of ProtoFilWW
Drupal core
PLUGINS
Import data
Reports Access control
Other services...
PROTOFILWW
SQL
XLS, TXT, CSV
Export dataXLS, TXT, CSV Solr/LuceneViews Solr Backend
Views
XML
Relational Database
UIMA
Contend Management component
• Open source Content Management System (CMS) and
Framework (CMF)
• Highly modular and with high extensibility
• Built in the PHP scripting language
WWTP Sample
1. Filamentous bacteria
2. Protozoa
3. Metazoa
4. Physical-chemical
5. Sample characterization
User roles
use case visitors collaborators WWTP researchers administrators
Find studies and results x x x x
Contact researchers x x x
Analysis of available data x
Data insertion x x
Creation of reports x
Export data x
Managing users x
Backup data x
Text Mining x x x x
Dynamic reporting and charting
Reports creation Reports display
Geolocation of the WWTPs
Address geocoding Map display
Text Mining
componentListing the species
mentioned in a
document
Major Text Mining technologies used
• Lucene is a high-performance text search engine
library.
• Solr is a standalone enterprise search server with a
REST-like API
• UIMA is a powerful infrastructure for the storage,
transport, and retrieval of document and annotation
knowledge accumulated in NLP pipeline systems
• LINNAEUS is a popular organism name identification
system for biomedical literature that is capable of
normalizing to unambiguous NCBI taxonomy identifiers
Text Mining process in ProtoFilWW
Solr/Lucene
LINNAEUS
Solr UIMA
PMC Open Access SubsetPMC Open Access Subset Solr XML documentsSolr XML documents
XPath convertion
Solr LINNAEUS Annotator
UIMA Component Descriptor Editor plugin
UIMA type system for LINNAEUS
LINNAEUS UIMA wrapper running on CVD
Drupal Views Solr Backend
Major contributions
1. The Web-based computational system
www.protofilww.org
2. The Drupal module Views Solr Backend
3. The Solr UIMA plug-in for LINNAEUS Annotator
Preventive Medicine
Alert the user to the risk of Type 2 Diabetes.
How?
1. We know the user has a gene mutation associated with Type 2
Diabetes, because he gave us is genome!
2. We know what he has eaten, because he told us!
3. We know what exercise he’s been doing, because he told us!
4. Genehome connects the dots!