Cytokine detection software tools | Immune system data analysis
Cytokines are proteins or micromolecular polypeptides mainly secreted by immune cells. They play an important regulatory role in many cellular activities, such as growth, differentiation, and interactions between cells. Research on cytokine identification and classification has important theoretical and practical significance that may assist in the elucidation of immune regulatory mechanisms at the molecular level and contribute to disease prevention, diagnosis, and treatment.
Provides a parallel coordinates visualization tool. Early Bird allows users to upload their data sets in CSV files, or to visualize data stored from selected studies. Early Bird hosts a large immunological data set based on about 240 individuals from a clinical cohort of 740 healthy aging adults. It contains data from cellular, protein, and genomic assays, with particular emphasis on stimulation-response assays (phosphoepitope analysis of cytokine signaling, and cytokine production and gene expression from stimulated PBMC). Early Bird is freely available online.
Predicts the cytokines and classifies them into families and subfamilies. CytoPred is a web server consisting in a method for predicting the cytokine based on Hybrid approach of PSI-BLAST and Support Vector Machine (SVM). Users can select the prediction approach and make predictions for multiple sequences at a time.
Predicts and classifies cytokines from protein sequence. CTKPred is a web server implementing a support vector machine (SVM)-based method developed for the recognition of cytokines on the basis of dipeptide composition. The software uses a three-step strategy for recognizing cytokines from protein sequences and further classifying cytokines to subfamily level. It was trained using fixed-length vectors obtained on the basis of the dipeptide composition of proteins.
Detects cytokine-receptor interactions. CytoSVM is a model based on the statistical learning algorithm, support vector machine (SVM), for identifying cytokine-receptor interactions on the basis of protein primary sequences. The software also provides optional function of prediction by protein names. CytoSVM broadens the understanding of cytokines’ physiological activities in the systematic level. It was applied to screen the whole genomes of human and mouse for novel cytokine-receptor pairs.