Sökning: "biology learning"
Visar resultat 1 - 5 av 169 avhandlingar innehållade orden biology learning.
1. Prediction of zinc-binding sites in proteins and efficient protein structure description and comparison
Sammanfattning : A large number of proteins require certain metals to stabilize their structures or to function properly. About one third of all proteins in the Protein Data Bank (PDB) contain metals and it is estimated that approximately the same proportion of all proteins are metalloproteins. LÄS MER
2. Advancing systems biology of yeast through machine learning and comparative genomics
Sammanfattning : Synthetic biology has played a pivotal role in accomplishing the production of high value commodities, pharmaceuticals, and bulk chemicals. Fueled by the breakthrough of synthetic biology and metabolic engineering, Saccharomyces cerevisiae and various other yeasts (such as Yarrowia lipolytica , Pichia pastoris ) have been proven to be promising microbial cell factories and are frequently used in scientific studies. LÄS MER
3. Attention and Learning through the Eyes of the Emotional Brain
Sammanfattning : The present thesis consists of four articles that address cognitive-emotional interactions as measured through eye movements and pupil dilation.Social facilitation-inhibition is an effect that describes changes in performance (enhancement or impairment) when individuals complete tasks in social presence compared to when they perform the same tasks in solitary conditions. LÄS MER
4. Machine Learning Enabled Functional Discovery in Yeast Systems Biology
Sammanfattning : Saccharomyces cerevisiae is a well-studied organism, yet roughly 20 percent of its proteins remain poorly characterized. Recent studies also seem to indicate that the pace of functional discovery is slow. LÄS MER
5. Manifold Learning in Computational Biology
Sammanfattning : This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions to various machine learning tasks. LÄS MER