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.

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
Shivateja Medisetti 16:00
Michael Wolf 17:00

Summary deadline: 21.10.2014




Discovering microRNAs from deep sequencing data using miRDeep.

Tutor: Andreas Keller

Student: Yvonne Saara Gladbach

miReader: Discovering Novel miRNAs in Species without Sequenced Genome.

Tutor: Andreas Keller

Student: Toner Arslan

Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients.

Tutor: Andreas Keller

Student: Adnan Javed

Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer

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

Tutor:  Christina Backes

Student: Mustafa Kahraman

Ensemble classifier based on context specific miRNA regulation modules: a new method for cancer outcome prediction

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.

Tutor: Christina Backes

Student: Sneha Benjamini

A systems’ biology approach to study microRNA-mediated gene regulatory networks

Tutor: Valentina Galata

Student: Tariq Khaleeq

Prediction of therapeutic microRNA based on the human metabolic network:

Tutor: Valentina Galata

Student: Alexander Gress

Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach:

Tutor: Valentina Galata

Student: Menglin Zheng