Advist - Advanced Data Handling and Visualization Techniques (IN2379)

 

Type:

Lecture (2 SWS) + Exercises (3 SWS)

Ects:

6.0

Curriculum:

M.Sc. Bioinformatics

Lecturer

Lothar Richter , Dmitrii Nechaev

Rotation:

Friday, 9:30 - 11:00 (lecture)
Friday: 12.15 -14.30 (exercise)

Place:

Lecture: Friday: online

Exercise: Friday: online

Exam:

tbd, 90 minutes working time

Language:

Englisch

Announcements:

--- Cancellation of lecture and exercise on May 14th. --- 
This Friday,  both the lecture and the exercise have to be cancelled due to scheduling conflicts. Next lecture takes place on Friday, May 21st.  

Lecture start is on April 23rd, 9.30 am.
Please join us at ADVIST-BBB

After successful completion of the module students are able to:

  • create pipelines for data extraction and integration from the bioinformatics resources
  • apply techniques of efficient data processing
  • analyze the data and create visualizations of their analyses
  • evaluate and apply visualization techniques
  • select appropriate NoSQL solutions with regards to their data
Topics:
  • Pythonics
  • Vectorization
  • Biological Databases
  • Pandas
  • NoSQL Databases
  • Machine Learning - Intro
  • Interactive Visualization
  • Presenting and Serving Models Models

Slides:Pythonics II.

  1. 23.04 - Intro
  2. 30.04 - Pythonics I.
  3. 07.05 - Pythonics II.
  4. 14.05 - No lecture
  5. 21.05 - Primary Databases I
  6. 28.05. - PDB & Secondary Databases
  7. 04.06 - NumPy
  8. 11.06 - Pandas NB1 NB2 Pandas Cheat Sheet Tidy Data
  9. 18.06 - NoSQL Compressed Notebooks (MongoDBs & SettingWithCopyWarning)
  10. 25.06 - Machine Learning & Common Sense Performance Measures
  11. 02.07 - Visualization
  12. 09.07 - Animated Plots MongoDB Demo

Exercise sheets:

  1. 23.04 - Intro
  2. 30.04 - Visualization, Homework
  3. 07.05 - Translation & Transcription, Homework
  4. 12.05 - No exercise
  5. 19.05 - Excise Genbank & Uniprot
  6. 26.05 - PDB
  7. 04.06 - NumPy
  8. 11.06 - Pandas
  9. 25.05 - Linear Regression MongoDB E. coli-Seqs