fix issue #19, update promoters metadata (#78)

* removes promoters, fixing issue #19 * updates to ml.bio promoters metadata * remove the column instance * remove promoters from dataset list * remove instance from feature list Co-authored-by: Trang Le <[email protected]>
EpistasisLab · Aug 18, 2020 · 223569e · 223569e
1 parent 94187a0
commit 223569e
Show file tree

Hide file tree

Showing 7 changed files with 87 additions and 149 deletions.
diff --git a/datasets/molecular_biology_promoters/metadata.yaml b/datasets/molecular_biology_promoters/metadata.yaml
@@ -1,19 +1,96 @@
 #Generated automatically by pmlb/write_metadata.py
 dataset: molecular_biology_promoters
-description: None yet. See our contributing guide to help us add one.
-source: None yet. See our contributing guide to help us add one.
-publication: None yet. See our contributing guide to help us add one.
+description: >
+    Title of Database: E. coli promoter gene sequences (DNA)
+                      with associated imperfect domain theory
+    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).
+
+    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
+
+
+    Number of Instances: 106
+
+    Number of Attributes: 59
+       -- class (positive or negative)
+       -- instance name
+       -- 57 sequential nucleotide ("base-pair") positions
+
+    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}.
+                     Code: a=0; c=1; g=2; t=3.
+
+source: >
+    Creators:
+
+    1. promoter instances: C. Harley (CHARLEY '@' McMaster.CA) and R. Reynolds
+
+    2. non-promoter instances and domain theory: M. Noordewier
+    -- (non-promoters derived from work of lab of Prof. Tom Record, University of Wisconsin Biochemistry Department)
+
+publication: >
+    Harley, C. and Reynolds, R. 1987. "Analysis of E. Coli Promoter Sequences." Nucleic Acids Research, 15:2343-2361.
+    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).
+
 task: classification
 target:
   type: binary
-  description: None yet. See our contributing guide to help us add one.
-  code: None yet. See our contributing guide to help us add one.
+  description: Positive class indicates a promoter.
+  code: -:1, +:0 (promoter)
 features: # list of features in the dataset
-  - name: instance
-    type: categorical
-    description: null # optional but recommended, what the feature measures/indicates, unit
-    code: null # optional, coding information, e.g., Control = 0, Case = 1
-    transform: ~ # optional, any transformation performed on the feature, e.g., log scaled
   - name: p-50
     type: categorical
   - name: p-49

diff --git a/datasets/molecular_biology_promoters/molecular_biology_promoters.tsv.gz b/datasets/molecular_biology_promoters/molecular_biology_promoters.tsv.gz
diff --git a/datasets/promoters/README.md b/datasets/promoters/README.md
diff --git a/datasets/promoters/metadata.yaml b/datasets/promoters/metadata.yaml
diff --git a/datasets/promoters/promoters.tsv.gz b/datasets/promoters/promoters.tsv.gz
diff --git a/datasets/promoters/summary_stats.csv b/datasets/promoters/summary_stats.csv
diff --git a/pmlb/dataset_lists.py b/pmlb/dataset_lists.py
@@ -156,7 +156,6 @@
     'prnn_fglass',
     'prnn_synth',
     'profb',
-    'promoters',
     'ring',
     'saheart',
     'satimage',