Sökning: "Disease consensus module"
Hittade 4 uppsatser innehållade orden Disease consensus module.
1. Comparing consensus modules using S2B and MODifieR
Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : It is currently understood that diseases are typically not caused by rogue errors in genetics but have both molecular and environmental causes from myriad overlapping interactions within an interactome. Genetic errors, such as that seen by a single-nucleotide polymorphism can lead to a dysfunctional cell, which in turn can lead to systemic disruptions that result in disease phenotypes. LÄS MER
2. Evaluating the biological relevance of disease consensus modules : An in silico study of IBD pathology using a bioinformatics approach
Kandidat-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : Inflammatory bowel disease encompasses a variety of heterogeneous chronic inflammatory diseases that affect the gastrointestinal tract, where Crohn’s disease and ulcerative colitis are the principal examples. The etiology of these, and many other complex human diseases, remain largely unknown and therefore pose relevant targets for novel research strategies. LÄS MER
3. Karakterisering av riskfaktorer kopplade till multipel skleros med hjälp av sjukdoms-moduler
Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : Multiple sclerosis is a common neurological disorder, characterized by increasing disability over time for the affected patient. The disease is considered an autoimmune disorder in which the immune system causes damage to nerves in the central nervous system through demyelination and inflammation. LÄS MER
4. Developing a web based tool for identification of disease modules
Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : Complex diseases such as cancer or obesity are thought to be caused by abnormalities in multiple genes and cannot be derived to one specific location in the genome. It has been shown that identification of disease associated genes can be made through looking at interaction patterns in a protein‐protein interaction network, where the disease associated genes are represented in clusters, or disease modules. LÄS MER