JAMIE (Joint Analysis of Multiple IP Experiments) is a R package to perform the joint analysis. The genome is assumed to consist of background and potential binding regions (PBRs). PBRs have context-dependent probabilities to become bona fide binding sites in individual datasets. This model captures the correlation among datasets, which provides basis for sharing information across experiments. Real data tests illustrate the advantage of JAMIE over a strategy that analyzes individual datasets separately.
SBEAMS is a framework for collecting, storing, and accessing data produced by a wide variety of experiments. The software provides a customizable framework to meet the needs of modern systems biology research.
SBEAMS – Microarray provides MIAME-compliant Affymetrix GeneChip microarray database functionality under the SBEAMS framework.
SBEAMS-Proteomics is part of the SBEAMS (Systems Biology Experiment Analysis Management System) Project, which is a framework for collecting, storing, and accessing data produced by a variety of different experiments; these experiments can be managed separately but then correlated later under the same framework.
The Well Layout program lets you describe a 96-well experiment using a graphical user interface.Layouts (and object in them) can be stored in a persistent Postgres SQL database or they can be stored in CSV-format files on a local hard drive.
CISMM (Computer Integrated Systems for Microscopy and Manipulation)
The Virtual NMJ is a simulation of an experiment recording the electrical potentials associated with neuromuscular transmission at the skeletal neuromuscular junction. The simulation allows you to observe the muscle action potential (AP) and endplate potentials (EPPs) evoked by either nerve stimulation or by direct current stimulation of the muscle fibre. The effects of a variety of drugs and of changes to ionic composition of the extracellular solution on the AP and EPPs can be studied.
MARQ (Microarray Rank Query) is an online microarray retrieval tool based on rank statistics. Datasets in MARQ, most of them retrieved from GEO, are processed into signatures, which are lists of genes ranked by their level of differential expression. Each dataset defines one of more of these signatures based on the possible comparisons of its constituent samples.