New! FABA 1.6 --- Functional Analysis By Association
Discover gene functions by mining data from different sources

In silico two-hybrid
Download FABA 1.6

With FABA you can discover your favorite genes' functions by analyzing thousands of public microarray data. Other researchers have done the hard work for you. They spent years and millions of dollars collecting data. You can do the fun part: analyzing their data and make original discoveries. You don't even need to ask for the data. We have done some initial work for you. We have collected thousands of microarray data from a number of public depositories. All you need to do is sit back, click, and wait a couple of minutes for amazing results that might take you years to discover.

We have optimized our software so well. FABA can mine Gigabytes of microarray data on your personal computer (PC, Mac, etc.) without any need of super computing power.

For more information about FABA 1.6, please click here.

MricoHelper 1.02
Order MricoHelper 1.02
MicroHelper 1.02 is also part of the BioToolKit 300.
Click here to download full-functional demo.
     Researchers with hands-on experiences in analyzing microarray data know well that a great amount of time is spent on merging datasets, checking data integrity, filtering noises, and normalizing data. MicroHelper 1.02 provides an user-friendly tool for these tasks. Beginners should appreciate that no programming language is required and professionals will appreciate the convenience as well.

Available for both PC and Mac.

MicroHelper 1.02 provides the following functions:

  • 1. Merge Data from raw datasets
         (a) Reads a variety of data formats;
         (b) Check Godlists (gene/spot info) for identities of arrays used;
         (c) Merge raw data into a single file.

  • 2. Filtrate
         (a) Reads a variety of data formats;
         (b) Options for "ceiling" and "flooring" to limit impact of outliers;
         (c) Options for filtering based on "variation" and missing data.
  • 3. Normalize Data
         (a) Normalize data such that different arrays can be compared.
         (b) Works for data in both log and unlog scales.
         (c) Normalization can be done in the presence of missing data.
  • 4. Transform
         (a) Transforms data from or to "Unlog", log2, or log10 scales;
         (b) Mean centering, divide by mean, or divide by standard derivations;
         (c) Works in the presence of missing data.
  • 5. Fill-in Missing Data
         Fills in missing data with 0, 1, row means, or column means.
  • 6. Select Subset
         Select or remove a subset of data based on a user provided list for a specific info field ( e.g., a list of accession number or gene names).
  • 7. Delete Control
         Removes user defined controls from a dataset.
  • 8. Annotate
         Record user comments about the data and analysis procedures.
  • 9. Data View
         Displays results in a table.
  • 10. Project Log
         Project Log records all steps (and details) taken to manipulate the data.
         If you would like to see additional functions included in future release of MicroHelper, please send us your suggestions.

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