X-jobb projects

We are currently working of protein structure and function prediction in several areas. Most of our work is focused on the development of improved methods in bioinformatics. We need students with different background, but It is a clear advantage if you at least have some programming experience. Below follows a short list of subject areas. If you want to know more please contact me.

• Protein fold recognition methods
• Studies of protein folding
• Homology modelling methods
• Molecular dynamics of membrane proteins
• Membrane proteins
• Studies of protein domain-graphs
• Comparative genomics of the peroxisomal proteome.

For more information check my papers or see the list of reports below.

Form for evaluation

Here is the form used for evaluation.

Finished exjobbs and other type of reports

Here is a list of all earlier xjobbs in my group.

1996-1999

• Robert Garemyr: The glycophorin A transmembrane domain dimer: A modelling study by MD-simulations. (1996)
• Jeanette Hargbo Development of HMMs that use predicted secondary structures for fold recognition (1998)
• Björn Larsson, Development of HMMs that use multiple sequence alignments. (1999)
• Amin Bakali, A study of pairwise sequence alignment methods (1999)
• Daniel Öhman, A study of lattice and non-lattice models for protein folding (1999)
• Anders Larsson, How many membrane proteins are there ? 1999
• Magnus Rosenlund Properties of lipid facing and burried residues in membrane proteins (1999)

2000

• Ylva Sälde The use of alignments to detect proteins of the same fold
• Christian Andersson Prediction of gamma turns - a neural network and support vector machine approach
• Anna Thoren: Detection of functional links between membrane proteins.
• Annette Höglund: A computational method for analyzing microarray gene expression data using support vector machines.

2001

• Emil Olovsson: Generation of realistic protein structures from fragments.
• Christian Ottoson Predicting the structure of protein fragments
• Jesper Lundström: Consensus prediction for fold recognition methods.
• Magnus Nilsson: Use of Support vector machines for fold recognition methods.
• Olivia Eriksson: Development of methods to build sidechains in proteins.
• Maria Hedman: How to best align membrane proteins
• Björn Wallner: Development of methods to discriminate between correct and incorrect protein models.
• Caroline Ekblad:Search for Potential Vaccine candidates by Identification of Tumor associated MHC class I peptides using High-throughput Mass Spectrometry Approach.
• Thorsten Fallisch: Vorhersage der SCOP-Klassifizierung aus Alignmentdaten unter Verwendung neuronaler Netzwerke
• Pierre Dönnes: Prediction of MHC class I binding peptides, using a machine learning approach.

2002

• Julian Macoveanu: Creation of a HMMER-based fold recognition method for the paracel genesequencer.
• Kristofer Hallén: Predicting the structure of protein fragments
• Mark Gustafsson: Studies of membrane protein families
• Robin Wellin: Prediction of protein super secondary structures.
• Michael Meissner:Develpoment of an intergrated hierarchical protein family database

2003

• Mi Jia: Prediction of MHC class II binding peptides, using machine learning approaches.
• Håkan Viklund: Development of a modular HMM package.
• Rajshree Gururaj: Studies of membrane protein families
• Anton Forsberg: Studies of alternative transcription start codong in E. Coli.
• Anna Wallin: Development of a fragment based assembly approach.

2005

• Fredrik Johansson. "Development of a SVM based ProQ version"
• Vikram Kumar. "Development of prodiv-PHOBIUS"

Finished lic-avhandlingar

• Robert Garemyr ``A study of the electrostatic treatment in molecular dynamics simulations.'', Sept 1999
• Jakob Halaska `` BioScript3D - A Biomolecular Visualization & Animation Tool''