Project description:To investigate the mechanism by which the microalgae-yeast co-culture system promotes wastewater denitrification. We concluded that microalgae and yeast exhibit a mutually beneficial relationship in the co-culture system. Microalgae nitrogen metabolism can be influenced by both miRNA and mRNA, and the presence of yeast stimulates gene expression in microalgae.
Project description:This is a Random Forest algorithm-based machine learning model to predict lncRNAs from coding mRNAs in plant transcriptomic data. The model assigns 1 for coding sequences and 2 for long non-coding sequences. The prediction is performed using a combination of Open Reading Frame (ORF) based, Sequence-based and Codon-bias features. Users need to download the curated ONNX model and also need to convert the sequences into feature matrix as mentioned in PLIT paper (Deshpande et al. 2019) to make predictions on sequences from Zea Mays sequence data.
Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively Combination of these methods enabled the reconstruction of the complete genome sequence of M oxyfera from the metagenome and identification of the functionally relevant enzymes and genes
