|30 November 2016, 15.15 |
Using "Deep Learning" to analyse interactions between donor and recipient DNA that determine early and late heart transplant failure
The major types of pathological rejection after heart transplantation are acute cellular rejection (ACR) and anti-body-mediated rejection (AMR). Despite the known risk factors for ACR, it is not possible to predict which patients who will develop ACR and at what time point after transplant.
The immune response to an allograft is an ongoing dialogue between the innate and adaptive immune system. Cells of the innate immune system express invariant pathogen associated pattern recognition receptors that enable them to detect not only repeating structural units expressed by pathogens but also markers of tissue injury or damage associated molecular patterns, which results in up-regulating transcription of genes, and production of micro-RNAs. The use of next-generation sequencing (NGS) technologies for whole-genome analysis may provide further knowledge of human leukocyte antigen (HLA) genes or other regions of the genome which are related to the regulation of the immune response. Variation in the sequence of DNA between transplant recipients and their donor may be an explanation for the differences in the chances of progression transplant failure.
The development of methods such as deep learning for analysing the whole genome sequencing that can be brought into the clinical setting and be used as an instrument for better matching of donor organs to recipients could increase short and long-term survival. Furthermore, the immunosuppression may be personalised depending on the patient’s risk of rejection based on the genomic profile.
|2 November 2016 , 15.15 |
The flavor puzzle and symmetries: tips for a successful marriage
The mixing and mass patterns of fermions in the Standard Model is a long standing problem known as the flavor puzzle. One natural way to describe patterns in nature is through the help of symmetries. In the first part of this talk I will review some useful techniques (or tricks) that can be used when looking for such patterns. In the second part, I will be more concrete and present an extension of the Standard Model where several of the flavor issues are tackled and interesting predictions for LHC phenomenology are found.
|14 September 2016, 15.15 |
The first release of astrometric and photometric data from ESA's Gaia mission (pdf)
The Gaia satellite was launched by the European Space Agency in December 2013. Its goal is to map the positions, distances, motions, brightnesses, and colours of about one billion stars in the Milky Way Galaxy, as well as other point-like sources such as asteroids and distant quasars. The first results of the mission are released today, September 14, in the Gaia Archive. This Gaia Data Release 1 only uses the first 14 months of observations, out of the expected 60 to 120 months before the end of mission, and is therefore very preliminary and incomplete. In the talk I will briefly recall what Gaia is and describe how the data were derived, with some focus on activities where Lund is strongly involved. Examples of important new scientific results will be given.
| 4 May 2016, 15.15 |
Computational models for cell reprogramming (pdf)Abstract:
Embryonic stem cells (ESC) have the capacity to self-renew and remain pluripotent, while continuously providing a source of a variety of differentiated cell types. Understanding what governs these properties at the molecular level is crucial for stem cell biology and its application to regenerative medicine. Of particular relevance is to elucidate those molecular interactions, which govern the reprogramming of somatic cells back into stem cells. A few central transcription factors inside embryonic stem cells and reprogrammed stem cells (induced pluripotent stem (iPS) cells) are believed to control the cells' pluripotency. Characterizations of pluripotent state were put forward on both transcription factor and epigenetic levels. Whereas core players have been identified, it is desirable to map out gene regulatory networks, which govern the reprogramming of somatic cells as well as the early developmental decisions.
A computational approach can be used as a framework to explore the dynamics of a simplified network of the pluripotent cells with the aim to understand how stem cells differentiate and also how they can be reprogrammed from somatic cells. In this talk, I present computational models for core stem cell gene regulatory network, which shed light on regulatory mechanisms governing pluripotency acquisition through reprogramming.
| 6 April 2016, 15.15 |
Searches for dark matter mediators with DARKJETS, or: how to make the most of LHC data (pdf)
Caterina Doglioni (Dept of Physics)
| 2 March 2016, 15.15 |
Astrometric detection of exoplanets with Gaia Abstract:
Most of the ~2000 exoplanets known today have been discovered by observing radial velocity motions and/or transits. The astrometric shifts of stars due to planetary orbits have been detected so far only in very few cases, despite a long history of interest and claims. The Gaia satellite, launched in December 2013 and currently gathering data, measures stellar astrometry with unprecedented precision. It is estimated that ~20,000 planets will be detected at the end of its 5-year mission.
In this talk, I will review the basic concepts of exoplanet orbit determination, focusing on the astrometric method. I will explore Bayesian methods for fitting the orbital parameters of exoplanets, and assess their efficiency using simulated Gaia observations. I will introduce information-based criteria to determine the ranking of different models (star without planet, single planet with circular orbit, single planet with eccentric orbit, ...). Finally I will compare the Bayesian approach with the traditional one, which is based on least-squares fitting and on the likelihood-ratio test.