Computational tools evolve to reveal patterns in flu data

Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

BACKGROUND A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. METHODOLOGY/PRINCIPAL FINDINGS We show that hierarchical clustering that invo...

analyzing patterns of classroom interaction in efl classrooms in iran

با به کار گیری روش گفتما ن شنا سی در تحقیق حا ضر گفتا ر میا ن آموزگا را ن و زبا ن آموزا ن در کلا سهای زبا ن انگلیسی در ایرا ن مورد بررسی قرار گرفت. ا هداف تحقیق عبا رت بودند از: الف) شنا سا ئی سا ختارهای ارتبا ط گفتا ری میا ن معلمین و زبا ن آموزا ن ب) بررسی تا ثیر نقش جنسیت دبیرا ن و زبا ن آموزان بر سا ختا رهای ارتبا ط گفتا ری میا ن آنها پ) مشخص کردن اینکه آ یا آموزگاران غا لب بر این ارتبا ط گف...

Integrative Analysis of Microarray Data to Reveal Regulation Patterns in the Pathogenesis of Hepatocellular Carcinoma

Background/Aims The integration of multiple profiling data and the construction of a transcriptional regulatory network may provide additional insights into the molecular mechanisms of hepatocellular carcinoma (HCC). The present study was conducted to investigate the deregulation of genes and the transcriptional regulatory network in HCC. Methods An integrated analysis of HCC gene expression ...

Computational tools to investigate genetic cardiac channelopathies

The aim of this perspective article is to share with the community of ion channel scientists our thoughts and expectations regarding the increasing role that computational tools will play in the future of our field. The opinions and comments detailed here are the result of a 3-day long international exploratory workshop that took place in October 2013 and that was supported by the Swiss Nationa...

Computational Intelligence Tools for Processing Collective Data J.UCS Special Issue