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cell types
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assay protocol
Self-Organizing Maps
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Add An Experiment
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Adding Compounds and Batches
Adding Results to the Database
Making a dilution series plate
Browing the SMA (Spinal Muscular Atrophy) data
SLIMS Database, supplemental material for Chemistry and Biology

This database constitutes the supplemental material for the Chemistry and Biology paper, Indoprofen Upregulates The Survival Motor Neuron (SMN) Protein Through a Cyclooxeganse Independent Mechanism

This database contains all of the screening data and analyses used to generate the results in this paper.

To use, first install SLIMS from http://slims.sourceforge.net/  You may wish to install Java 1.4 from Sun in order to substructure search the dataset.  Java can be downloaded from http://www.java.com/

In this tutorial you will learn how to:

1) Navigate to the results section
2) Open up projects and their related experiments.
3) View dilution series results.
4) View primary screen results
5) Make a Self-Organiging Map
6) Peform a Medline Analysis

Here is a brief walkthrough of the dataset:

Navigate to the Results Set
The initial screen that will open is the main database screen.  You will not have to log into this database, you will automatically be logged in as administrator.

To view results, navigate to the results section by clicking on the results item in the navigation pane.  You will see the following window:

The results section is comprised of Projects, each of which may have several experiments.  There is only one project in this database, namely the SMA project.  To see the project experiments, either double click on the project or select the project and then select the experiments tab. 

Viewing Dilution Series
We will start off by selecting the Indoprofen Analog dilution series as shown below:

Naturally, we would like to see the dilution series.  Click on the dilution tab:

You will now see a collection of compounds, all of which contain dilution series.  To view a dilution series, select the compound of interest and then click on the Plot Dilution button from the commands menu.  For most selection criteria such as compound selection, you must select the desired row.  To select a row, click on the row label as shown in the image:

You will then see the following graph:

If you would like to make a Microsoft Excel report for the dilution series (and Microsoft Excel is installed in your system) , simply click on the To Excel button.  You will get a worksheet organized as follows:

Batch ID Vendor Catalogue Number Name


Therap cat:  Analgesic; anti-inflammatory

Average Standard Deviation Concentration Unit Values

0.913909 0.098091815 0.000305 uM 1.071891 0.858663 0.813809 1.036725 0.810129 0.905925 1.001003 0.877012 0.850027

0.994117 0.125856267 0.00061 uM 0.751704 1.120885 0.964472 1.082781 1.058371 0.940237 0.857238 1.103127 1.068233

0.975944 0.057272039 0.001221 uM 1.082242 0.929279 1.013926 0.931256 0.924118 0.948988 0.96355 0.94494 1.045203

1.063237 0.121272047 0.002441 uM 0.914557 1.193801 1.053489 1.051002 0.954975 1.098901 1.257361 1.132671 0.912372

0.98509 0.107714542 0.004883 uM 1.142967 1.006335 0.913637 0.851119 0.953363 0.847895 1.03078 0.984719 1.134998

1.032169 0.130544906 0.009766 uM 1.099953 1.073501 0.987704 1.236839 0.953133 0.960272 1.092892 1.108478 0.776749

0.9839 0.182872352 0.019531 uM 0.952281 1.275918 0.915477 1.197231 1.131371 0.759467 0.994722 0.840024 0.788613

1.038596 0.118107293 0.039063 uM 1.161138 0.849002 1.124795 1.030738 1.199994 0.933789 1.114526 0.966807 0.966574

0.954293 0.188731997 0.078125 uM 1.014386 0.882125 0.656246 1.039488 1.222792 0.718246 1.099405 1.100568 0.855377

1.051995 0.274185854 0.15625 uM 0.452218 1.162518 1.047509 0.895102 1.241905 0.997577 1.171753 1.05823 1.441138

1.260496 0.11891338 0.3125 uM 1.173789 1.162288 1.327902 1.187329 1.451922 1.170518 1.306911 1.143605 1.420201

1.352682 0.39262458 0.625 uM 1.263957 1.736647 0.807138 1.512716 1.348065 1.91778 1.327615 1.539772 0.720452

1.793127 0.263609834 1.25 uM 1.512608 1.728596 1.907321 1.896364 1.550021 2.326989 1.678885 1.555358 1.982

1.960254 0.371294419 2.5 uM 2.069485 1.951255 2.199906 2.534473 1.275757 2.028315 2.134838 1.513718 1.934544

2.707835 0.402670015 5 uM 1.980698 3.107103 2.523313 2.692676 2.981218 3.12215 2.208116 2.775266 2.979979

2.748159 0.152760948 10 uM 2.6006 2.975992 2.83384 2.726066 2.621058 2.90085 2.724087 2.840634 2.510301

Viewing Primary Screening Results

Go back to the experiments section by clicking on the Experiments tab.

Double click on the NINDS CLUC Screen to view the primary screening results of the NINDS CLUC screening data.  NINDS is a collection of bioactive compounds obtained from the National Institute of Neurological Disorders and Stroke.  The initial screen shows related comments, in this case it is the cell culture and compound seeding methods used to prepare the screen.

Notice the six tabs at the top of the screen.

This tab contains comments about the experiment.  This is a good place to place cell culture descriptions and various assay related information.
This tab shows a view of all the plates used in the dataset.  These plates also show the detected systematic error.  Any value below 0.05 is considered suspect and should be analyzed by hand.

If the dataset has been corrected, this view also shows the plates that have had systematic error removed.
This tab shows the raw data collected from each plate as well as the scored data.  This is a global view of the experiment and does not show any replicate statistic data.  The control wells are also present in this view.
If the data set has been loaded with the option to correct systematic error, this tab shows the raw data from each plate after the systematic error has been normalized.  Similar to the raw data, this tab does not show replicate data.  The control wells are also present in this view.
This tab shows the results organized by replicates.  For each batch (compound) in the dataset, this view sumarizes all the replicate data including the average and standard deviation of both the raw data and the scored data.  For instance, if the protocol was computing percent enhancement, this view shows the statistics for the percent enhancement for all batches (compounds) in the screen.
This is the same as the results tab except that it computes the score (i.e. percent enhancement) and raw data from the systematic error corrected plates.

Select the results data tab.  At this point you may want to make the scren larger to view more data.  Note that to the left and right of the data view there are sashes that you can drag to the left and right to increase the size of the viewed data.  See the image below.  Clicking on any header in the grid will sort the data in that column.  The first click will sort descending, the second will sort ascending and the third will revert to the original view.  Click on the mean_percent_enhancement tab.

After sorting the data, the view will look like this:

Now the data is sorted by the top compounds.  You might want to plot the data as well.  Click on the plot button in the commands menu.  Select "mean_percent_enhancement" for the Y axis and "batch_id" for the X.

Click ok.  You will see the following plot:

Click on a point in the plot will highlight the structure in the view window.  The box shown highlighted above is our friend Indoprofen which is one of the top hits from the NINDS dataset.  To see if there are any similar compounds to indoprofen, click on Find Similar in the commands menu.  This will compute a similarity score based on the compounds fingerprint and rank all compounds relative to the selected structure.  A Similarity score of 0 indicates that there is no difference in fingerprint while a score of 1 means that the fingerprints have nothing in common.  note: this is normally called a diference score.

Now from the newly created Similarituy view, make a new plot, this time with Similarity Score as the Y axis and mean percent enhancement as the X axis.  You will see the following plot.

The highlighted compound at the bottom (at Similarity score 0) is indoprofen.  Note that this compound stands alone.  There are no compounds clustered near this data point indicating that the structure of indoprofen is highly different than any other structure in the NINDS data set.

Making a SOM
Final, we will make a self-organizing map in order to browse through the dataset.  A self organizing map is an analysis technique that is used to place similar compounds together in space.  The SOM is a collection of connecting nodes where nodes closer together are generally more similar than nodes farther apart.

To create a SOM, click on the analyze button in the commands pane.  You have two options at this point, View Self Organizing map or Create self organizing map.  Viewing an existing map will allow you to plate compounds located in a quicklist.  This is useful if you have already created a SOM and wish to see where new compounds fall.  Click on Create Self Organizing Map.  You will see a wizard at this point.

Clicking on Next will show you the current compound set that you are going to use to create the SOM.

Note that the SOM only uses the compounds fingerprint to generate the data.  Click on Next to set the creation options.

In general, the default values are appropriate to use.  Remember that the size of the map (Map size rows and Map size cols) above, the number of iterations and the number of compounds will influence the time it takes to generate a self organizing map.  Once the map has been started, you will not be able to stop the operatation until the generation of the map has completed.  You may click on Quick SOM to make the map faster at the expense of quality, although this might be appropriate for browsing.

Enter a name for the SOM such as NINDS CLUC Dataset and click on next.  This map will take about five to ten minutes to build on a current computer (1.5gHz to 2.0gHz PC).

When the SOM is complete, click on finish and the SOM will appear (Note, due to the random nature of SOM generation, the map you see will look not look exactly as follows)  You can resize the window if it is too small.  The map is initially colored by the number of compounds in a node.  Red has the most and dark blue has the least.  Holding the cursor over a node will indicate how many compounds are in a well.

Clicking on a well will show the compounds in the well, for example this node has compounds with a Dihydroxyflavone motif:

The som can also be recolored based on various data.  Click on the SOM menu and then click on recolor.  Choose mean_percent_enhancement

Then choose your favorite coloring scheme:

The map will then be recolored using the selected criteria:

Clicking on the light blue hits (purple, indigo...) wil reveal clusters of higher scoring compounds.  We immediately find indoprofen using this technique:

Note that, in general, this is not a good way to find singlular hits, but is intended to find clusters of hits with similar structures.

Perform A Medline Analysis

Now, go back to the results tab and click on search and find all compounds that have greater than 60% percent enhancement:

Set the column to "Mean_percent_enhancement" and the expression to ">" then set the value to 60.  Click on Search for All.  Inspect the newly created Search tab and then click on Analyze and select Search Medline Database.

You will be presented with a list of drug names.  These only appear if your selected drugs actually do have names, if they do not, then you cannot search medline.  Obviously, if the drug name is novel and does not appear in Medline, you will not find any results either.

The next step is to remove all salts/base and acids identifiers from the drug names as well as any extraneous information.  Simply edit the text in the window and click on Search. 

You will be presented with the Medline Search result seen below.  Each mechanism link takes you to the relevant papers in PubMed.  Notice that there is at least on Cyclooxegenase result from the Indoprofen compound.  This table is a good way to organize mechanisms with hit compounds.  Unfortunately, you need to screen compounds such as the Active Compound Library for maximum effectiveness when using the Medline Searching Capabillity.  The index Medline papers only go through 2002, we are in the process of indexing 2003 and will release the index when it is available.

Medline Analysis

Medline Annotation v 1.0
mechanism literature percentile compound percentile score %hits %drugs num selected drugs num Library drugs num selected papers num Library papers selected mean selected median selected std Library mean Library median Library std pos neg epos eneg drug drug
ANTIBIOTICS 3.00E-001 3.00E-001 9.00E-002 0.1111 0.0602 1 177 1 194 1.0000 1.0000 NAN 1.5763 1.5763 NAN 1 176 0.5418 176.4582 ACLARUBICIN
ANTIOXIDANTS 3.00E-001 3.00E-001 9.00E-002 0.1111 0.0231 1 73 1 66 1.0000 1.0000 NAN 1.4795 1.4795 NAN 1 67 0.2082 67.7918 ACLARUBICIN
PROTEIN SYNTHESIS 4.00E-001 4.00E-001 1.60E-001 0.1111 0.0143 1 42 1 39 1.0000 1.0000 NAN 1.3095 1.3095 NAN 1 41 0.1286 41.8714 ACLARUBICIN
DNA 5.00E-001 5.00E-001 2.50E-001 0.1111 0.1167 1 359 1 659 1.0000 1.0000 NAN 2.6657 2.6657 NAN 1 342 1.0500 341.9500 ACLARUBICIN
GLYCOSYLATION 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0082 1 25 1 25 1.0000 1.0000 NAN 1.3200 1.3200 NAN 1 23 0.0735 23.9265 ACLARUBICIN
UP 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0898 1 281 1 267 1.0000 1.0000 NAN 1.4270 1.4270 NAN 1 263 0.8082 263.1918 RHAPONTIN
ANTI-INFLAMMATORY AGENTS 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0412 1 129 1 135 1.0000 1.0000 NAN 1.6744 1.6744 NAN 1 120 0.3704 120.6296 INDOPROFEN
PHOSPHATASE 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0231 1 74 1 56 1.0000 1.0000 NAN 1.4324 1.4324 NAN 1 67 0.2082 67.7918 RHAPONTIN
ANTIBIOTIC 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0316 1 93 1 91 1.0000 1.0000 NAN 1.4839 1.4839 NAN 1 92 0.2847 92.7153 ACLARUBICIN
CDK2 5.00E-001 5.00E-001 2.50E-001 0.1111 0.0041 1 12 1 9 1.0000 1.0000 NAN 1.3333 1.3333 NAN 1 11 0.0367 11.9633 RHAPONTIN
JUN 7.00E-001 7.00E-001 4.90E-001 0.1111 0.0932 1 287 1 410 1.0000 1.0000 NAN 1.6481 1.6481 NAN 1 273 0.8388 273.1612 ANISINDIONE
CDK6 1 1 1 0.1111 0.0007 1 2 1 2 1.0000 1.0000 NAN 1.0000 1.0000 NAN 1 1 0.0061 1.9939 RHAPONTIN
ANTICOAGULANTS 1 1 1 0.1111 0.0082 1 26 1 24 1.0000 1.0000 NAN 1.4231 1.4231 NAN 1 23 0.0735 23.9265 ANISINDIONE
CYCLOOXYGENASE 1 1 1 0.2222 0.0221 2 69 2 59 1.0000 1.0000 0 1.4638 1.4638 1.5008 2 63 0.1990 64.8010 INDOPROFEN RHAPONTIN
CELL CYCLE 1 1 1 0.1111 0.0214 1 63 1 67 1.0000 1.0000 NAN 2.0952 2.0952 NAN 1 62 0.1929 62.8071 RHAPONTIN
TF 1 1 1 0.1111 0.0058 1 18 1 16 1.0000 1.0000 NAN 1.1111 1.1111 NAN 1 16 0.0520 16.9480 ANISINDIONE
ANTICARCINOGENIC AGENTS 1 1 1 0.1111 0.0037 1 11 1 11 1.0000 1.0000 NAN 1.0909 1.0909 NAN 1 10 0.0337 10.9663 RHAPONTIN

Missing Drugs






That is it for the introduction.  Feel free to play with different analyses and colorings.

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