Biomarker Discovery: a machine learning workflow applied to Tuberculosis diagnosis.

In our previous work, while working in tuberculosis diagnostics research, we developed some workflows to detect possible biomarkers using Omics data from large cohort studies. Discovered in 19th century, Tuberculosis (TB) is still a serious public health problem and it is estimated that one third of the World’s population is infected with Mycobacterium Tuberculosis (mTB). A... Continue Reading →

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High Dimensional Data & Hierarchical Regression

In a high-throughput experiment one performs measurements on thousands of variables (e.g. genes or proteins) across two or more experimental conditions. In bioinformatics, we come across such data generated using technologies like Microarrays, Next generation sequencing, Mass spec etc. Data from these technologies have their own pre-processing, normalising and quality checks (see here and here... Continue Reading →

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