Biological preprocessing

Index Entries Fungal upgrading engineered storage biological preprocessing Pleurotus ostreatus straw composite. 

Each of the two technologies has its own perquisite for successful application to biological samples, which includes extraction and isolation of RNA or metabolite and their measurement and preprocessing of the obtained data. These methods are briefly summarized in the following paragraphs. 

After these preprocessing steps, raw data can be used for biological interpretation. In a typical experiment comparing two conditions, raw gene expression data is converted to log 2 fold-changes. Significances are calculated with different statistical tests. 

Pattern recognition techniques can be divided into display, preprocessing, supervised, and unsupervised learning. Pattern recognition methods are used among others in the search for correlations between sequence, structure, and biological activity in cheminformatics and bioinformatics. 

Given the same dataset, different choices of preprocessing, clustering algorithms, and distance measures could lead to varied clustering results. Therefore, the assessment of cluster validity is of utmost important. However, in practice, the cluster quality is hard to evaluate, particularly in the analysis of biological data. 

The chemical structures for a given biological target and project code are retrieved from the main database and preprocessed (SMILES canonicalized, duplicates, and invalid entries removed). 

---