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Type | Seminar (2 SWS) |
ECTS | 4.0 |
Lecturer | Burkhard Rost, Maximilan Hecht |
Time | Monday, 12:00 - 13:30 |
Room | MI 01.09.034 |
Language | English |
Application / Registration
Application is organised centrally for all bioinformatics seminars. After you have been assigned to our seminar, we will distribute the topics.
Topics related to the research interests of the group: protein sequence analysis, sequence based predictions, protein structure prediction and analysis; interaction networks.
The Pre-meeting will be held on Jul 21sr at 11 am in Room MI 01.09.034
The rules and hints for preparation of the seminar discussed in the pre-meeting are also summarised in our Checklist and on these slides (update Jul 21st).
Final Schedule
Date | Topic | Supervisor | Student |
---|---|---|---|
Oct 19 |
Biological Databases
|
Cejuela | Wentzig |
Oct 26 |
Predicting subcellular localization using functional hierarchies
|
Goldberg | Wirth |
Protein localization prediction from evolutionary profiles
|
Goldberg | Werner | |
Nov 2 |
Protein disorder — a breakthrough invention of evolution?
|
Goldberg | Maier |
Mass-spectrometry-based draft of the human proteome
|
Kloppmann | Ren | |
Nov 9 |
CRISPR/Cas
|
Reeb/Richter | Sturm |
Single Cell Sequencing
|
Reeb | Hadziahmetovic | |
Nov 16 |
Robustness and evolvability of proteins
|
Hecht | Madin |
Predicting functional effects of sequence variants
|
Hecht | Zwiebel | |
Nov 23 |
PolyPhobius: Prediction of transmembrane helices in protein sequences
|
Reeb | Giurgiu |
Observations in Fold Space |
Schafferhans |
de Motte | |
Nov 30 |
HIV Mutational Pathways
|
Richter | Sigl |
Conditional random fields for named entity recognition
|
Cejuela |
Gilicze |
Juan Miguel Cejuela
We will look into one specific problem of text mining and research discovery: the recognition of mutations in publications. Simple mentions of mutations such as SNPs like "A32G" are easy to recognize with regular expressions or rule-based approaches (see for example the system MutationFinder). However, more complex mentions that use natural language still pose an unsolved challenge (e.g. "a homozygous complex mutation in Family B that consisted of a deletion of GC at codon 48 (exon 2) with the insertion of 25 bp (c.143–144delGCins25)"). Moreoever, implementation and evaluation of mutation finders in full-text articles is also scarse to nonexistent. In this seminar, we will look into the latest state-of-the-art systems for mutation mention recognition, [2]. These systems are machine-learning-based and typically apply Conditional Random Fields (CRFs) [1] for named-entity recognition. We will look at the challenges of recognizing natural mentions and different types of mutations: single substitutions, multiple substitutions, insertions, deletions, translocations, etc. Finally, we will discuss the importance of building succesful text mining systems for mutation recognition. Note that this seminar may require some programming (in Java or C++) to have a hands-on experience in constructing and applying CRFs.
Juan Miguel Cejuela
Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories. This seminar shall give an overview of different Databases, how to access them and problems associated.
Identification of a protein’s subcellular localization is an important step towards elucidating its function. In this seminar, a machine-learning-based method for predicting localization in prokaryotes and eukaryotes shall be presented. The method is original in incorporating a hierarchical ontology of subcellular localization classes. Furthermore, it uses predicted features like the secondary structure of a protein and evolutionary information in form of sequence profiles to improve prediction accuracy considerably.
Literature:
Alberts B, Bray D, Lewis J, Raff M, Roberts K, Watson JD. Molecular Biology of the Cell. New York: Garland Science, 2002
Nair R, Rost B (2005). Mimicking cellular sorting improves prediction of subcellular localization. J Mol Biol. Apr 22;348(1):85-100. www.ncbi.nlm.nih.gov/pubmed/15808855
Identification of a protein’s subcellular localization is an important step towards elucidating its function. In this seminar, a machine-learning-based methods for predicting localization in prokaryotes and eukaryotes shall be presented. The methods incorporate a hierarchical ontology of subcellular localization classes. The predictions are derived from evolutionary infromation (Loctree2/3) as well as from the powerful sequence homology-based BLAST (Loctree3).
Literature:
The regions in proteins that do not adopt regular three-dimensional structures in isolation are called disordered regions. In this seminar the functional and structural aspects of disordered proteins shall be discussed. Though only one literature source is provided, the student is expected to use and refer to in his presentation to additional sources for a detailed understanding of protein disorder.
Literature:
Using mass-spectrometry, researchers from TUM have produced an almost complete inventory of the human proteome. This information is now freely available in the ProteomicsDB database, which is a joint development of TUM and software company SAP. The database includes information for example on the types, distribution, and abundance of proteins in various cells and tissues as well as in body fluids. The talk shall briefly introduce mass-spectrometry and then focus on the results of the publication below and the ProteomicsDB.
Literature:
Jonas Reeb
PolyPhobius uses hidden markov models (HMMs) to predict transmembrane helices in protein sequences. This talk shall introduce transmembrane proteins, HMMs and sequence-based transmembrane helix prediction at the example of PolyPhobius.
Literature:
Maximilian Hecht
Mutations are the catalysts of evolution. Phenotypes need to be robust against mutation in order to prevail. On the other hand, species need to be able to adapt their phenotypes to changing selection pressure. Therefore, robustness seems to be the opposite of evolvability. This topic is aimed at explaining the complex relationship between robustness and evolvability in proteins in the light of tolerating mutations at certain positions while being sensitive at others. The given literature is merely a starting point for further reading and should not be considered complete.
Literature:
Jonas Reeb / Lothar Richter
Clustered regularly interspaced short palindromic repeat (CRISPR) technology, a microbial defense system, has been developed based on its remarkable ability to bring the endonuclease Cas9 to specific locations within complex genomes by a short RNA, to precisely edit the genome, to build toolkits for synthetic biology, and to monitor DNA in live cells. This seminar is a presentation of the underlying principles and possible applications.
Jonas Reeb
Whereas genome approaches in many case are extended to meta-genome approaches also an specialization towards the opposite direction exists. Single cell sequencing acknowledge the fact of diversity in tissue and cell populations. This talk will present this new approach.
Maximilian Hecht
Elucidating the effects of naturally occurring genetic variation on the wild-type cellular function is one of the major challenges in personalized medicine. This talk shall explain how variant effects can be predicted and how this can help to further our understanding of naturally occuring variation and disease. The given literature is merely a starting point for further reading and should not be considered complete.
Literature:
Andrea Schafferhans
Lothar Richter
HIV is the causing agent for AIDS and still not curable. A lot of research has been done to understand the underlying molecular mechanisms and to elucidate the basis of aquired resistance to anti-viral drugs. The talk should cover some computational approaches to detect and to predict mutation pathways leading to resistance against various types of anti-viral agents. The given literature should serve as a starting point for more recent developments in the field.