Bioinformatics for miRNA Diagnostics
The Seminar will take place at the beginning of October for one or two days depending on the number of pariticpants. To receive the “Schein” you need to give a talk of about 45 minutes, write a summary of the topic, and also attend to all talks.
The first meeting, where you can select a topic, will take place at 06.05.14 at 13:00 h in the terminal room, second floor of Building E2.1.
The seminar will take place on 13.10./14.10.14 in building E2.1 room 106.
UPDATE
The seminar will take place on 14.10.14 in building E2.1 room 106, we start at 8:00 a.m..
Participant | Time slot |
Yvonne Saara Gladbach | 8:00 |
Adnan Javed | 9:00 |
Mustafa Kahraman | 10:00 |
Sneha Benjamini | 11:00 |
Tariq Khaleeq | 13:00 |
Alexander Gress | 14:00 |
Menglin Zheng | 15:00 |
Summary deadline: 21.10.2014
Topics:
Discovering microRNAs from deep sequencing data using miRDeep.
http://www.ncbi.nlm.nih.gov/pubmed/18392026
Tutor: Andreas Keller
Student: Yvonne Saara Gladbach
miReader: Discovering Novel miRNAs in Species without Sequenced Genome.
http://www.ncbi.nlm.nih.gov/pubmed/23805282
Tutor: Andreas Keller
Student: Toner Arslan
Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients.
http://www.ncbi.nlm.nih.gov/pubmed/22027949
Tutor: Andreas Keller
Student: Adnan Javed
Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer
http://www.translational-medicine.com/content/12/1/66
Tutor: Christina Backes
Student: Shivateja Medisetti
mirExplorer: Detecting microRNAs from genome and next generation sequencing data using the AdaBoost method with transition probability matrix and combined features
https://www.landesbioscience.com/journals/rnabiology/article/16026/?nocache=595132767
Tutor: Christina Backes
Student: Mustafa Kahraman
Ensemble classifier based on context specific miRNA regulation modules: a new method for cancer outcome prediction
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3848894/
Tutor: Christina Backes
Student: Michael Wolf
SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells.
http://nar.oxfordjournals.org/content/38/5/e34.long
Tutor: Christina Backes
Student: Sneha Benjamini
A systems’ biology approach to study microRNA-mediated gene regulatory networks
http://www.ncbi.nlm.nih.gov/pubmed/24350286
Tutor: Valentina Galata
Student: Tariq Khaleeq
Prediction of therapeutic microRNA based on the human metabolic network:
http://www.ncbi.nlm.nih.gov/pubmed/24403541
Tutor: Valentina Galata
Student: Alexander Gress
Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach:
http://www.biomedcentral.com/1471-2105/15/S1/S4
Tutor: Valentina Galata
Student: Menglin Zheng