1 - 16 of 16 results

Decision Forest

Outperforms decision tree in both training and validation. Decision forest is an ensemble method developed by combining the predictions from multiple independent decision tree models to reach a better prediction. This method yields much high prediction accuracy in the high confidence regions compared to decision tree. Decision forest generally gives higher positive predictivity than other method, and even higher positive predictivity within definable high confidence regions.


Converts common peptide identification files (mzIdentML, pepXML, mzTAB) to the proBAM or proBED format. proBAMconvert reads files using pyteomics or a self-build parser. The software automatically recognizes the protein identifiers used in the identification file. These identifiers must comply with guidelines adapted from commonly used software. It also provides various customization options in order to accommodate output to specific needs (i.e. allowing mutation, 3-frame translation mapping, removing duplicated mapping …).

GPTime / Gaussian Process Time

Predicts chromatographic retention time with gaussian processes. GPTime is a kernel based Bayesian framework that can learn a non-linear mapping between input and target values. GPTimes has provided with a natural framework for estimating the uncertainty of predictions. To obtain predicted retention time and predicted standard deviation of test peptides, GPTime package allows researchers to either train their own GP model or use one of the pre-trained models included in the package.

JS-MS / JavaScript Mass Spectrometry

Allows visualization of specialized tree dimensional mass spectrometry (MS). JS-MS runs as a web application without the need for any external dependencies. It is able to display mass-to-charge (m/z), retention time (RT) and intensity dimensions. This tool allows users to zoom, scroll, and rotate graphs permitting full navigation of even the largest MS data sets. Users can customize the view range and perspective of the graph with a variety of graph transformations.

CIG-P / Circular Interaction Graph for Proteomics

Generates circular diagrams for visually appealing final representation of affinity-purification mass spectrometry (AP-MS) data. CIG-P is aids to present AP-MS data to a wider audience and envisions that the tool finds other applications too, e.g. kinase – substrate relationships as a function of perturbation. The strength of this method is the ability to integrate orthogonal datasets with each other, e.g. affinity purification data of kinase PRPF4B in relation to the functional components of the spliceosome.

FAST-AIMS / Fully Automated Software Tool for Artificial Intelligence in Mass Spectrometry

Allows automated predictive analysis of mass spectrometry data. FAST-AIMS offers a sequence of analysis in aid of developing protocol standardization for proteomic data analysis. The software can (a) generate a classification model by optimizing the parameters of analysis algorithms to ensure its optimal performance; (b) obtain an unbiased estimate of the future classification performance of the optimized model; (c) generate a model and estimate classification performance in tandem; and (d) apply an existing model to a new set of samples.