Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

Discovery and visualization of miRNA–mRNA functional modules within integrated data using bicluster analysis

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression at a post-transcriptional level. An miRNA may target many messenger RNA (mRNA) transcripts, and each transcript may be targeted by multiple miRNAs. Our understanding of miRNA regulation is evolving to consider modules of miRNAs that regulate groups of functionally related mRNAs. Here we expand the model of miRNA...

Gene expression data analysis using novel methods: Predicting time delayed correlations and evolutionarily conserved functional modules

Declaration I hereby declare that the dissertation entitled " Gene expression data analysis using novel methods: Predicting time delayed correlations and evolutionarily conserved functional modules " submitted to the Department of Biology, Philipps-Universität, Marburg is the original and independent work carried out by me under the guidance of the PhD committee, and the dissertation is not for...

Ccc-bicluster Analysis for Time Series Gene Expression Data

Many of the biclustering problems have been shown to be NP-complete. However, when they are interested in identify biclusters in time series expression data, it can limit the problem by finding only maximal biclusters with contiguous columns. This restriction leads to a well-mannered problem. Its motivation is the fact that biological processes start and conclude in an identifiable contiguous p...

Using Literature and Data to Annotate and Learn Bayesian Networks

Integration of remote sensing and meteorological data to predict flooding time using deep learning algorithm

Accurate flood forecasting is a vital need to reduce its risks. Due to the complicated structure of flood and river flow, it is somehow difficult to solve this problem. Artificial neural networks, such as frequent neural networks, offer good performance in time series data. In recent years, the use of Long Short Term Memory networks hase attracted much attention due to the faults of frequent ne...