1. Biomedical Text Mining and Its Applications
By: Raul Rodriguez-Esteban
Presented By: Ankita Tanwar

2. INTRODUCTION & MOTIVATION
Tutorial for Biologists and Computational Biologists
Main motivation to spread awareness
Introduces to term BioNLP
Introduces main concepts in Text Mining
Lists multiple tools like Whatizit, GoPubMed, GoGene, …

3. TEXT MINING: MAIN CONCEPTS
Term & Term Recognization
Tools: Whatizit, Abner, GoPubMed/GoGene, …
Relationships between terms
Tools: MedGene, BioGene, Endeavour, G2G, …
Discovering Relationships
Tool: Arrowsmith
Measure of output Quality
F-Measure, i.e., harmonic mean between precision and recall
Comprehensive text mining
Sources of information: Medline and beyond.

4. EXAMPLES OF TEXT RECOGNITION

5. Focusing on Tool GoPubMed
By: Ralph Delfs, Andreas Doms, Alexander Kozlenkov, and Michael Schroeder

6. INTRODUCTION
Allows finding information needed through the use of biomedical background knowledge.
It doesn't rank, the user does!
It retrieves PubMed abstracts for user’s search query and sorts relevant information to the 4 top level categories:
What
Who
Where
When

7. MOTIVATION
The biomedical literature grows at a tremendous rate and PubMed comprises over abstracts
Approaches such as protein interactions, pathways, and micro array data aim to improve literature search
But, these approaches do not mimic human information foraging

8. CONTRIBUTIONS
Introduction and realization of ontology-based literature search
Derived a term-extraction algorithm
Derived an induced ontology from the extracted terms

9. Structure of GENE ONTOLOGY

10. GoPubMed: Main Idea
The main idea is to use GeneOntology to search and browse PubMed
Problems to be solved:
How to extract GeneOntology terms from PubMed abstract
How to construct the relevant sub-ontology of GO

11. GoPubMed: Term Extraction
Use of Regular Expression:
\w matches a word
\s a space
the dot . any single character
To repeatedly match an expression there are three operators:
? requires the preceding pattern to appear once or not at all
+ requires it to appear once at least once
* requires it to appear any number of times (including 0)

12. Term Extraction: Example
Keyword searched: cAMP-dependent kinase
Seed term: kinase activity
Seed Child: cAMP-dependent protein kinase activity
Method to search for such a pattern:
kinase \w+
cAMP-dependent .* kinase activity

13. GoPubMed: Induced Ontology
Used to avoid unnecessary parts of ontology not relevant to given abstracts.
Given an ontology, 𝑂 and a set of terms 𝑇′′, extracted from abstracts, construct a minimal sub-ontology of 𝑂
Find all the intermediate terms, from terms in 𝑇′′ to root

14. Screenshot of Initial Prototype

15. Screenshot of Current Application

16. THANK YOU!!