Module1 - Overview:
- Technical skills:
- Understand and practice how to extract data from Medline and prepare the raw data through Pubmed Parser.
- Read and understand scientific papers: deepen understanding of biometrical relationships between entities such as drugs, genes and phenotypes.
- Python: learned python coding and how to use Python to access web data.
- Dependency-parsing: learned what Dependency Parsing is and what is the difference between Pubmed Parser and Stanford Parser.
- Medline: learned database of Medline and how to extract data from it.
- EBC:Learned what Ensemble Biclustering for Classification (EBC) and hierarchical clustering algorithms are and how they work as well as what is the advantage of EBC compared to other classifiers that don’t account for the semantic relatedness of different dependency paths.
- STEM-AWAY website: get more information for further study.
- Soft Skills:
- Getting more familiar with the STEM-AWAY website and communication skills, more interaction with other team members.
- Independence: Finished the presentation for Journal club prompts along with other team members, and gained more confidence.
- Learned how to use Medline to get the raw data and use Pubmed Parser to prepare the raw data.
- Finished Journal club prompts and built up some fundamentals.
- Learned how to use Github and Git.
- Raised my interests in bioinformatics after I read and studied the papers listed in the Prerequisites forum.
- Deepen understanding the background of bioinformatics and Data Visualization.
- Finished Journal club prompts.
- Completed raw data preparation for the next module to use.
Goals for The Upcoming Week:
- Raw data parsing.