Attention!The date for the presentations is fixed: 29/04/2020 08:00 a.m. st. Note that the presentations will be held in an online format to which you will receive an invitation mail. Please also note that you have to attend all talks to qualify for the certificate.Attention!
Cancer is a heterogeneous class of pathologies that can affect nearly all tissues in the human body. These diseases are generally characterized by a common set of features, known as the Hallmarks of cancer (Hanahan and Weinberg 2000 and 2011). The hallmarks constitute properties, cancer cells often acquire during their development. These are often caused by an interplay of miscellaneous molecular and (epi-)genetic aberrations.
Using modern high-throuput technologies, we are now able to measure different properties of cancer cells at relatively low cost. This development facilitated the creation of huge international projects, such as The Cancer Genome Atlas (TCGA), that try to catalog the genomic landscape of thousands of cancers across many disease types. The tremendous amount of the generated datasets and their high dimensionality make a manual evaluation impossible. Therefore, the development of automated and robust bioinformatics methods for the analysis of these datasets has become a necessity.
In this seminar you will learn how bioinformatics approaches can be used to study the molecular mechanisms of cancer and thereby improve our knowledge of biological processes that are responsible for tumor initiation and progression. Each participant will present a research paper that covers an interesting computational method to categorize tumors, to identify pathogenic mechanisms, or to find novel biomarkers that improve the diagnostic of the disease.
The seminar will be held as a block seminar the week before the lectures start.
In order to participate in the seminar you are required to attend the first meeting.
There the topics are distributed. No prior registration or reservation is possible.
Please confirm your participation in the seminar until 2020/01/31 via mail to teaching@bioinf.uni-sb.de.
Also, you have to register in HISPOS until 2020/02/14.
# | Paper | Autoren | |
---|---|---|---|
1 | Designing string-of-beads vaccines with optimal spacers. | Schubert et al. | |
2 | Identifying drug effects via pathway alterations using an integer linear programming optimization formulation on phosphoproteomic data. | Mitsos et al. | |
3 | Metagenes and molecular pattern discovery using matrix factorization. | Brunet et al. | |
4 | Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization | Wang et al. | |
5 | Optimal structural inference of signaling pathways from unordered and overlapping gene sets | Acharya et al. | |
6 | A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction | Haider et al. | |
7 | Single-cell RNA-seq denoising using a deep count autoencoder | Eraslan et al. | |
8 | OncoNEM: inferring tumor evolution from single-cell sequencing data | Ross and Markowetz | |
9 | Tree inference for single-cell data | Jahn et al. | |
10 | Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics | Street et al. |