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- GENOM 2005 v3.42
- This is the full cracked version of the software. Download, extract, install, enjoy.
- Inside the archive there is "crack" folder wich contains everything you need to crack the software.
- Download link:
- http://filemates.com/dxdrfoamg3xl/GENOM.2005.v3.42.cracked.rar
- Genom 2005 is a feature rich and user friendly application for analysing array-experiments (e.g. from provider Affymetrix).
- Many publications have been released about our previous developed program gEn0M (GENOM 2005 is the successor of gEn0M). Please take a look at the publications page for some of them.
- Features for microarray analysis software
- Analysis of AffyMetrix-Arrays (cDNA-Arrays or similar technologies could be easily integrated as well)
- Normalisation of raw data
- Many additional gene information (official gene names, location, function prediction, sequences, database references (GeneOntology, InterPro, SwissPROT, ENSEMBL, GeneBank...)
- Multiple analysis methods (cluster, Support-Vector-Machine, statistical methods (e.g. TTest))
- Automatic pathway mapping (BioCarta, GenMAPP, KEGG...)
- Integrated pathway editor (user friendly drag and drop operation)
- Function prediction
- Sequence analysis
- expression data table
- Genom 2005 presents the data in different colours for each signal, so you have a quick overview of the data. Also a gene name and an accession number for each probeset is presented concurrently.
- gene expression graph
- This is a diagram with one array. It shows a bar for each probeset.
- 3D View
- You can display each signal on your array in a 3D view. When comparing it with another array you can easily find interesting probesets. You can also sort the signals by gene function or gene location.
- Chromosome
- This view displays all probesets orders by their location on the chromosome.
- Gene expression process
- This screenshot shows a graph where every probeset is represented by a line. It shows the up/down regulation of a gene between different time.
- Pathway View
- This screenshot shows a loaded pathway which is directly combined with the array data you have loaded.
- Pathway Editor
- With this integrated map editor, you can easily create new pathways or edit existing one.
- Gene function prediction
- Often you have no information about a probeset because it's an EST or it has not been analysed before. With this module you can get new information from probesets or custom sequences over a BLAST search (online). Possible new gene functions will then be shown.
- function prediction details
- Details about the function prediction.
- PubMED research
- PubMED is the largest database in the world with medical articles (hosted on Ncbi website). This module searches that database and returns relevant results to the entered term (or gene).
- MeSH research
- MeSH (Medical Subject Headings) provides ordered terms to improve PubMED searches for example.
- Gene Network
- The relationship of the genes described in the abstracts from PubMED are shown here as relationship diagram.
- Gene functions for microarray
- This algorithm presents the data in a table with all the gene functions from the genes you previously filtered, or can be done for the whole array.
- GO for array
- This displays the gene functions in a GeneOntology like view.
- Probeset information
- The gene information dialog. Here you get more detail information from the searched query like sequence, description and more.
- Probeset details
- In this screenshot, you can directly access the links for more information about your query. Unlike in other programs you can click on a link and directly access the result page without filling out web forms.
- functions for probeset
- Another GeneOntology graph of the gene functions from the gene.
- internet research
- In this screenshot you can see direct links for more information about your query. Unlike in other programs you can click on a link and get directly to the result page without filling out web forms.
- Cluster
- This cluster can be made easily. It shows the most equal values paired together in a graph.
- Scatterplot
- Another view from the cluster algorithm.
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