array analyzer
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Key Features:
- import of data
- filtering of the data: missing values, standard deviation, absolute value, variation filter
- data transformation: replicates, missing values, logarithm, data normalization, divide by mean, subtract mean, z- transformation
- analysis of significance and comparisons
- k-means and hierarchical clustering
- annotation of the genes with information from primary databases and text extracted information
Description:
Metalife Array Analyzer provides a computational and graphical environment for storing, preprocessing, analyzing, clustering and
saving results from DNA microarray experiments. The program can organize and analyze the data in a number of different ways dedicated to
helping researchers design and analyze expression profiling experiments to generate high-quality, statistically sound, and biologically
interesting results.
Clusters of genes can be analyzed with respect to common features and common concepts among subsets of genes. Time courses can be mapped on pathways. Hidden correlations within and between sets of experimental data can be automatically analyzed in minimal time. The need to manually revise annotations, extensively scan literature to uncover complex correlations in an unmanageable amount of data is dramatically reduced.
Micro-arrays are revolutionizing the drug development. This technology helps in cancer research. For example, studying the different expressions of genes in tumor and normal cells may lead to new discoveries of drugs that are targeting the molecular characteristics of the cancer rather than focusing on the conventional cytotoxic agents.
Different than the common applications for analysis of array data, Metalife Array Analyzer combines both conventional mathematical, statistical clustering algorithms and clustering based on classified annotated information.
It profits strongly from the information content of the metalife knowledge base. The information is derived both from integrated databases and extracted from text and is used to automatically annotate biological objects.
This enriched body of information is subject to Metalife's advanced classification. The ontology based multi-dimensional classification builds the framework for a new method of functional clustering. Due to the fast functional analysis, statistical parameters can be adjusted in an iterative process to optimize results and improve the quality of analyses.
Clusters of genes can be analyzed with respect to common features and common concepts among subsets of genes. Time courses can be mapped on pathways. Hidden correlations within and between sets of experimental data can be automatically analyzed in minimal time. The need to manually revise annotations, extensively scan literature to uncover complex correlations in an unmanageable amount of data is dramatically reduced.
Micro-arrays are revolutionizing the drug development. This technology helps in cancer research. For example, studying the different expressions of genes in tumor and normal cells may lead to new discoveries of drugs that are targeting the molecular characteristics of the cancer rather than focusing on the conventional cytotoxic agents.
Different than the common applications for analysis of array data, Metalife Array Analyzer combines both conventional mathematical, statistical clustering algorithms and clustering based on classified annotated information.
It profits strongly from the information content of the metalife knowledge base. The information is derived both from integrated databases and extracted from text and is used to automatically annotate biological objects.
This enriched body of information is subject to Metalife's advanced classification. The ontology based multi-dimensional classification builds the framework for a new method of functional clustering. Due to the fast functional analysis, statistical parameters can be adjusted in an iterative process to optimize results and improve the quality of analyses.
Order installation of local copy of Array Analyzer!
Metalife offers installation of local copy of its products upon licensing. Ordering a local copy benefits private users with the following extra advantages:
- Data security ensured by the management of all analyses and sources locally in your organization's secured network.
- Impossibility of competitor companies to track down your searches in public resources and reveal your interests.
- Custom development of project specific GUI features, new functionalities, DB sources.
- Completely new decisions implementation upon request.