| From Eddie at Irvine... Ronnyk
| 1. Title of Database: E. coli promoter gene sequences (DNA)
|                       with associated imperfect domain theory
|
| 2. Sources:
|    (a) Creators:
|        - promoter instances: C. Harley (CHARLEY@McMaster.CA) and R. Reynolds
|        - non-promoter instances and domain theory: M. Noordewier
|          -- (non-promoters derived from work of lab of Prof. Tom Record,
|              University of Wisconsin Biochemistry Department)
|    (b) Donor: M. Noordewier and J. Shavlik, {noordewi,shavlik}@cs.wisc.edu
|    (c) Date received: 6/30/90
|
| 3. Past Usage:
|    (a) biological:
|        -- Harley, C. and Reynolds, R. 1987.
|           "Analysis of E. Coli Promoter Sequences."
|           Nucleic Acids Research, 15:2343-2361.
|        machine learning:
|        -- Towell, G., Shavlik, J. and Noordewier, M. 1990.
|           "Refinement of Approximate Domain Theories by Knowledge-Based
|           Artificial Neural Networks." In Proceedings of the Eighth National
|           Conference on Artificial Intelligence (AAAI-90).
|    (b) attributes predicted: member/non-member of class of sequences with
|        biological promoter activity (promoters initiate the process of gene
|        expression).
|    (c) Results of study indicated that machine learning techniques (neural
|        networks, nearest neighbor, contributors' KBANN system) performed as
|        well/better than classification based on canonical pattern matching
|        (method used in biological literature).
|
| 4. Relevant Information Paragraph:
|    This dataset has been developed to help evaluate a "hybrid" learning
|    algorithm ("KBANN") that uses examples to inductively refine preexisting
|    knowledge.  Using a "leave-one-out" methodology, the following errors
|    were produced by various ML algorithms.  (See Towell, Shavlik, &
|    Noordewier, 1990, for details.)
|
| 	    System	 Errors		Comments
| 	    ------	 ------		--------
| 	     KBANN	  4/106		a hybrid ML system
| 	     BP		  8/106		std backprop with one hidden layer
| 	     O'Neill	 12/106		ad hoc technique from the bio. lit.
| 	     Near-Neigh  13/106		a nearest-neighbor algo (k=3)
| 	     ID3	 19/106		Quinlan's decision-tree builder
|
|    Type of domain: non-numeric, nominal (one of A, G, T, C)
|    -- Note: DNA nucleotides can be grouped into a hierarchy, as shown below:
|
| 		      X (any)
| 		    /   \
| 	  (purine) R     Y (pyrimidine)
| 		  / \   / \
| 		 A   G T   C
|
|
| 5. Number of Instances: 106
|
| 6. Number of Attributes: 59
|    -- class (positive or negative)
|    -- instance name
|    -- 57 sequential nucleotide ("base-pair") positions
|
| 7. Attribute information:
|    -- Statistics for numeric domains: No numeric features used.
|    -- Statistics for non-numeric domains
|       -- Frequencies:  Promoters Non-Promoters
|                        --------- -------------
|                A        27.7%     24.4%
|                G        20.0%     25.4%
|                T        30.2%     26.5%
|                C        22.1%     23.7%
|
|    Attribute #:  Description:
|    ============  ============
|              1   One of {+/-}, indicating the class ("+" = promoter).
|              2   The instance name (non-promoters named by position in the
|                  1500-long nucleotide sequence provided by T. Record).
|           3-59   The remaining 57 fields are the sequence, starting at
|                  position -50 (p-50) and ending at position +7 (p7). Each of
|                  these fields is filled by one of {a, g, t, c}.
|
| 8. Missing Attribute Values: none
|
| 9. Class Distribution: 50% (53 positive instances, 53 negative instances)

+,-

attr 01 : a,g,t,c
attr 02 : a,g,t,c
attr 03 : a,g,t,c
attr 04 : a,g,t,c
attr 05 : a,g,t,c
attr 06 : a,g,t,c
attr 07 : a,g,t,c
attr 08 : a,g,t,c
attr 09 : a,g,t,c
attr 10 : a,g,t,c
attr 11 : a,g,t,c
attr 12 : a,g,t,c
attr 13 : a,g,t,c
attr 14 : a,g,t,c
attr 15 : a,g,t,c
attr 16 : a,g,t,c
attr 17 : a,g,t,c
attr 18 : a,g,t,c
attr 19 : a,g,t,c
attr 20 : a,g,t,c
attr 21 : a,g,t,c
attr 22 : a,g,t,c
attr 23 : a,g,t,c
attr 24 : a,g,t,c
attr 25 : a,g,t,c
attr 26 : a,g,t,c
attr 27 : a,g,t,c
attr 28 : a,g,t,c
attr 29 : a,g,t,c
attr 30 : a,g,t,c
attr 31 : a,g,t,c
attr 32 : a,g,t,c
attr 33 : a,g,t,c
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attr 35 : a,g,t,c
attr 36 : a,g,t,c
attr 37 : a,g,t,c
attr 38 : a,g,t,c
attr 39 : a,g,t,c
attr 40 : a,g,t,c
attr 41 : a,g,t,c
attr 42 : a,g,t,c
attr 43 : a,g,t,c
attr 44 : a,g,t,c
attr 45 : a,g,t,c
attr 46 : a,g,t,c
attr 47 : a,g,t,c
attr 48 : a,g,t,c
attr 49 : a,g,t,c
attr 50 : a,g,t,c
attr 51 : a,g,t,c
attr 52 : a,g,t,c
attr 53 : a,g,t,c
attr 54 : a,g,t,c
attr 55 : a,g,t,c
attr 56 : a,g,t,c
attr 57 : a,g,t,c