PDF Output of CLIC (Clustering by Inferred Co-Expression)

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PDF Output of CLIC (clustering by inferred co-expression) Dataset: Num of genes in input gene set: 13 Total number of genes: 16493 CLIC PDF output has three sections: 1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set. Red lines shows the partition of input genes into CEMs, ordered by CEM strength. Each row shows one gene, and the brightness of squares indicates its correlations with other genes. Gene symbols are shown at left side and on the top of the heatmap. 2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets. Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows). Each column is one GEO series dataset, sorted by their posterior probability of being selected. The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset. CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score. 3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset. Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Overview of Co-Expression Modules (CEMs) with Dataset Weighting Scale of average Pearson correlations Num of Genes in Query Geneset: 13. Num of CEMs: 0. 0.0 0.2 0.4 0.6 0.8 1.0 Gtf2f1 Ccnc Med21 Polr2a Smarca4 Crebbp Ercc3 Kat2b Gtf2b Smarca2 Gtf2h3 Smarcb1 Cdk8 Gtf2f1 Ccnc Med21 Polr2a Smarca4 Crebbp Ercc3 Singletons Kat2b Gtf2b Smarca2 Gtf2h3 Smarcb1 Cdk8.

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ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Universitat Autònoma de Barcelona Departament de Bioquímica i Biologia Molecular Institut de Biotecnologia i Biomedicina HUMAN PRION-LIKE PROTEINS AND THEIR RELEVANCE IN DISEASE Doctoral thesis presented by Cristina Batlle Carreras for the degree of PhD in Biochemistry, Molecular Biology and Biomedicine from the Universitat Autònoma de Barcelona. The work described herein has been performed in the Department of Biochemistry and Molecular Biology and in the Institute of Biotechnology and Biomedicine, supervised by Prof. Salvador Ventura i Zamora. Cristina Batlle Carreras Prof. Salvador Ventura i Zamora Bellaterra, 2020 Protein Folding and Conformational Diseases Lab. This work was financed with the fellowship “Formación de Profesorado Universitario” by “Ministerio de Ciencia, Innovación y Universidades”. This work is licensed under a Creative Commons Attributions-NonCommercial-ShareAlike 4.0 (CC BY-NC- SA 4.0) International License. The extent of this license does not apply to the copyrighted publications and images reproduced with permission. (CC BY-NC-SA 4.0) Batlle, Cristina: Human prion-like proteins and their relevance in disease. Doctoral Thesis, Universitat Autònoma de Barcelona (2020) English summary ENGLISH SUMMARY Prion-like proteins have attracted significant attention in the last years.
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