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Physical Modeling of Protein Folding

Popular Abstract in Swedish Sekvensbaserade proteinveckningsmodeller utvecklas och testas på peptider med både betablad- och alfahelix-struktur, samt på små helix-proteiner. Modellernas potentialer är minimalistiska och baseras huvudsakligen på vätebindningar och effektiva hydrofobicitetskrafter. Den geometriska representationen av proteinkedjan är däremot detaljerad. Vi studerar det termodynamiskSequence-based models for protein folding are developed and tested on peptides with both alpha- and beta-structure, and on small three-helix-bundle proteins. The interaction potentials of the models are minimalistic and based mainly on hydrogen bonding and effective hydrophobicity forces. By contrast, the geometric representation of the protein chain is detailed. We explore the thermodynamic behav

The role of the customer order decoupling point in operations and supply chain management

In the field of operations and supply chain management (OSCM), the customer order decoupling point (CODP) hasi been recognized as an important strategic parameter for roughly 30 years. It is the point in the value chain where forecast-driven material flows get separated from order -driven material flows. Despite its long history in the field, multiple calls for further consideration of the CODP inIn the field of operations and supply chain management (OSCM), the customer order decoupling point (CODP) hasbeen recognized as an important strategic parameter for roughly 30 years. It is the point in the value chain whereforecast-driven material flows get separated from order-driven material flows. Despite its long history in the field,multiple calls for further consideration of the CODP in OSCM

A New Method for Mapping Optimization Problems onto Neural Networks

A novel modified method for obtaining approximate solutions to difficult optimization problems within the neural network paradigm is presented. We consider the graph partition and the travelling salesman problems. The key new ingredient is a reduction of solution space by one dimension by using graded neurons, thereby avoiding the destructive redundancy that has plagued these problems when using s

Vårt energirika universum

Högenergiastrofysik spelar en nyckelroll för vår förståelse av Universum. Den mest energirika strålningen avslöjar heta och våldsamma fenomen. Vi undersöker het gas i galaxhopar, som är de största och tyngsta objekten i Universum. Vi undersöker också het gas som samlas i skivor omkring supermassiva svarta hål i galaxers centra.Men högenergiastrofysik ger oss också viktig information om vår egen gaHigh Energy Astrophysics plays a key role in understanding the universe. These radiations reveal the processes in the hot and violent universe. High Energy Astrophysics probes hot gas in clusters of galaxies, which are the most massive objects in the universe. It also probes hot gas accreting around supermassive black holes in the centers of galaxies.Finally, high energy radiation provides importa

A somatic mutation of GFI1B identified in leukemia alters cell fate via a SPI1 (PU.1) centered genetic regulatory network.

We identify a mutation (D262N) in the erythroid-affiliated transcriptional repressor GFI1B, in an acute myeloid leukemia (AML) patient with antecedent myelodysplastic syndrome (MDS). The GFI1B-D262N mutant functionally antagonizes the transcriptional activity of wild-type GFI1B. GFI1B-D262N promoted myelomonocytic versus erythroid output from primary human hematopoietic precursors and enhanced cel

Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.

The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interactio

A modeling study on how cell division affects properties of epithelial tissues under isotropic growth.

Cell proliferation affects both cellular geometry and topology in a growing tissue, and hence rules for cell division are key to understanding multicellular development. Epithelial cell layers have for long times been used to investigate how cell proliferation leads to tissue-scale properties, including organism-independent distributions of cell areas and number of neighbors. We use a cell-based t

Hydrophobicity Patterns in Protein Folding

The protein folding problem is addressed focussing on the hydro- phobicity patterns in the amino acid sequences and structures. Both real and model proteins are investigated. The hydrophobicity pattern of real proteins is probed in two ways. First, it is asked which binary pattern is most conserved within groups of related proteins. Not unexpectedly, the most conserved patterns are strongly corre

Statistical Physics of Protein Folding and Aggregation

The mechanisms of protein folding and aggregation are investigated by computer simulations of all-atom and reduced models with sequence-based potentials. A quasi local Monte Carlo update is developed in order to efficiently sample proteins in the folded phase. A small helical protein, the B-domain of staphylococcal protein A, is studied using a reduced model. In the thermodynamically favoured topo

Modeling auxin transport and plant development

The plant hormone auxin plays a critical role in plant development. Central to its function is its distribution in plant tissues, which is, in turn, largely shaped by intercellular polar transport processes. Auxin transport relies on diffusive uptake as well as carrier-mediated transport via influx and efflux carriers. Mathematical models have been used to both refine our theoretical understanding

Combined Regularisation Techniques for Artificial Neural Networks

Artificial neural networks are prone to overfitting – the process of learning details specific to a particular training data set. Success in preventing overfitting through combining the L2 and dropout regularisation techniques has led to the combination’s recent popularity. However, with the introduction of each additional regularisation technique to an artificial neural network, there comes new h

Searching for Dark Photons with Jet

Standardmodellen är teorin som beskriver tre utav de fyra fundamentala naturkrafterna, och Standardmodellens komplettering har hittills varit partikelfysikens största prestation. Modellen integrerar fysikens mest elementära partiklar och deras interaktioner till en och samma teori. Den kan exempelvis beskriva universums tillstånd en kort stund efter den stora smällen, eller varför protonen inte ka