molecular_targets_data

Name: molecular_targets_data
Author: QSong-github

132stars4forks

How to install molecular_targets_data?

qsong-github/drugclaw/molecular_targets_data

$npx -y skills add QSong-github/DrugClaw --skill molecular_targets_data

Installs into the current project.

Summary

Query the NCI-60 Molecular Target (Protein) database from the Developmental Therapeutics Program. Use when the user asks about protein expression of drug targets across the NCI-60 cancer cell line panel, or wants to look up a gene, cell line, or cancer panel in the NCI DTP molecu

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SKILL.md

1	# NCI DTP Molecular Target Query Skill
2
3	Search NCI-60 protein-level molecular target data by any entity. Auto-detects type:
4
5	\| Input Pattern \| Detected As \| Match Logic \|
6	\|---\|---\|---\|
7	\| `EGFR`, `TP53` \| gene / protein \| exact on `GENE` or substring on `ENTITY_MEASURED`, `TITLE` \|
8	\| `MCF7`, `NCI-H460` \| cell line \| substring on `cellname` \|
9	\| `Breast`, `Leukemia` \| cancer panel \| substring on `pname` \|
10	\| `12345` (pure digits) \| MOLTID \| exact on `MOLTID` (NCI pattern #) \|
11
12	## Drug-Relevance Guide
13
14	Only protein expression data is downloaded — proteins are the direct molecular
15	targets of drugs (kinase inhibitors → kinase expression, antibodies → receptor levels).
16
17	\| Dataset \| Download? \| Reason \|
18	\|---\|---\|---\|
19	\| WEB_DATA_PROTEIN.ZIP \| YES \| Drug targets: protein expression across NCI-60 \|
20	\| WEB_DATA_ALL_MT.ZIP \| Optional \| Superset incl. enzyme activity (also drug-relevant) \|
21	\| WEB_DATA_DNA.ZIP \| No \| Genomic characterisation, not drug targets \|
22	\| WEB_DATA_SEQUENOM_METHYLATION.ZIP \| No \| Epigenetic; indirect \|
23	\| WEB_DATA_*_MIR.ZIP \| No \| microRNA regulation; indirect \|
24	\| WEB_DATA_METABOLON*.ZIP \| No \| Metabolomics; downstream, indirect \|
25	\| Microarray / SNP / CopyNum / Karyotype \| No \| Cell-line genomic profiling; indirect \|
26
27	## API
28
29	\| Function \| Input \| Returns \|
30	\|---\|---\|---\|
31	\| `load_data(path)` \| file or directory path \| `list[dict]` \|
32	\| `search(data, entity)` \| data + single entity string \| `list[dict]` \|
33	\| `search_batch(data, entities)` \| data + list of entity strings \| `dict[str, list[dict]]` \|
34	\| `summarize(hits, entity)` \| hit list + label \| compact LLM-readable text \|
35	\| `to_json(hits)` \| hit list \| `list[dict]` (JSON-serialisable) \|
36	\| `query(data, entities, top_n)` \| data + str or list \| text block \|
37
38	## Record Fields
39
40	Each record contains:
41
42	\| Field \| Description \|
43	\|---\|---\|
44	\| `MOLTID` \| NCI pattern number (molecular target ID) \|
45	\| `GENE` \| Gene symbol \|
46	\| `TITLE` \| Gene / protein full name \|
47	\| `MOLTNBR` \| NCI experiment ID \|
48	\| `PANELNBR` / `CELLNBR` \| Internal panel / cell identifiers \|
49	\| `pname` \| Cancer panel name (e.g., Breast, Leukemia) \|
50	\| `cellname` \| Cell line name (e.g., MCF7, A549/ATCC) \|
51	\| `ENTITY_MEASURED` \| What was measured (e.g., protein name) \|
52	\| `GeneID` \| NCBI Gene ID \|
53	\| `UNITS` \| Measurement units \|
54	\| `METHOD` \| Assay method \|
55	\| `VALUE` \| Numeric measurement value \|
56	\| `TEXT` \| Additional notes \|
57
58	## Usage
59
60	See `if __name__ == "__main__"` block in `16_NCI_DTP_MolTarget.py` for runnable
61	examples covering: single gene query, cell line profile, batch multi-target
62	search, cancer panel query, and JSON output.
63
64	## Quick Examples
65
66	```python
67	from importlib.machinery import SourceFileLoader
68	mt = SourceFileLoader("mt", "16_NCI_DTP_MolTarget.py").load_module()
69
70	data = mt.load_data()
71
72	# Single drug target
73	print(mt.query(data, "EGFR"))
74
75	# Multiple targets
76	print(mt.query(data, ["TP53", "BRAF", "HER2"]))
77
78	# Cell line molecular profile
79	print(mt.query(data, "MCF7"))
80
81	# JSON for downstream pipeline
82	import json
83	hits = mt.search(data, "EGFR")
84	print(json.dumps(mt.to_json(hits[:5]), indent=2))
85	```
86
87	## Data Source & Download
88
89	- Provider: NCI Developmental Therapeutics Program (DTP)
90	- URL: https://wiki.nci.nih.gov/spaces/NCIDTPdata/pages/155845004/Molecular+Target+Data
91	- File: `WEB_DATA_PROTEIN.TXT` (headerless CSV, comma-delimited)
92	- Local Path: `resources_metadata/dti/Molecular Target Data/WEB_DATA_PROTEIN.TXT`
93	- Format: comma-delimited, 14 columns (see Record Fields above)
94	- Auth: None (public domain, U.S. government)
95
96	### Download Commands
97
98	```bash
99	# File already at:
100	# resources_metadata/dti/Molecular Target Data/WEB_DATA_PROTEIN.TXT
101	```

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molecular_targets_data

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View on GitHub

How to install molecular_targets_data?

qsong-github/drugclaw/molecular_targets_data

$npx -y skills add QSong-github/DrugClaw --skill molecular_targets_data

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# NCI DTP Molecular Target Query Skill
2
3	Search NCI-60 protein-level molecular target data by any entity. Auto-detects type:
4
5	\| Input Pattern \| Detected As \| Match Logic \|
6	\|---\|---\|---\|
7	\| `EGFR`, `TP53` \| gene / protein \| exact on `GENE` or substring on `ENTITY_MEASURED`, `TITLE` \|
8	\| `MCF7`, `NCI-H460` \| cell line \| substring on `cellname` \|
9	\| `Breast`, `Leukemia` \| cancer panel \| substring on `pname` \|
10	\| `12345` (pure digits) \| MOLTID \| exact on `MOLTID` (NCI pattern #) \|
11
12	## Drug-Relevance Guide
13
14	Only protein expression data is downloaded — proteins are the direct molecular
15	targets of drugs (kinase inhibitors → kinase expression, antibodies → receptor levels).
16
17	\| Dataset \| Download? \| Reason \|
18	\|---\|---\|---\|
19	\| WEB_DATA_PROTEIN.ZIP \| YES \| Drug targets: protein expression across NCI-60 \|
20	\| WEB_DATA_ALL_MT.ZIP \| Optional \| Superset incl. enzyme activity (also drug-relevant) \|
21	\| WEB_DATA_DNA.ZIP \| No \| Genomic characterisation, not drug targets \|
22	\| WEB_DATA_SEQUENOM_METHYLATION.ZIP \| No \| Epigenetic; indirect \|
23	\| WEB_DATA_*_MIR.ZIP \| No \| microRNA regulation; indirect \|
24	\| WEB_DATA_METABOLON*.ZIP \| No \| Metabolomics; downstream, indirect \|
25	\| Microarray / SNP / CopyNum / Karyotype \| No \| Cell-line genomic profiling; indirect \|
26
27	## API
28
29	\| Function \| Input \| Returns \|
30	\|---\|---\|---\|
31	\| `load_data(path)` \| file or directory path \| `list[dict]` \|
32	\| `search(data, entity)` \| data + single entity string \| `list[dict]` \|
33	\| `search_batch(data, entities)` \| data + list of entity strings \| `dict[str, list[dict]]` \|
34	\| `summarize(hits, entity)` \| hit list + label \| compact LLM-readable text \|
35	\| `to_json(hits)` \| hit list \| `list[dict]` (JSON-serialisable) \|
36	\| `query(data, entities, top_n)` \| data + str or list \| text block \|
37
38	## Record Fields
39
40	Each record contains:
41
42	\| Field \| Description \|
43	\|---\|---\|
44	\| `MOLTID` \| NCI pattern number (molecular target ID) \|
45	\| `GENE` \| Gene symbol \|
46	\| `TITLE` \| Gene / protein full name \|
47	\| `MOLTNBR` \| NCI experiment ID \|
48	\| `PANELNBR` / `CELLNBR` \| Internal panel / cell identifiers \|
49	\| `pname` \| Cancer panel name (e.g., Breast, Leukemia) \|
50	\| `cellname` \| Cell line name (e.g., MCF7, A549/ATCC) \|
51	\| `ENTITY_MEASURED` \| What was measured (e.g., protein name) \|
52	\| `GeneID` \| NCBI Gene ID \|
53	\| `UNITS` \| Measurement units \|
54	\| `METHOD` \| Assay method \|
55	\| `VALUE` \| Numeric measurement value \|
56	\| `TEXT` \| Additional notes \|
57
58	## Usage
59
60	See `if __name__ == "__main__"` block in `16_NCI_DTP_MolTarget.py` for runnable
61	examples covering: single gene query, cell line profile, batch multi-target
62	search, cancer panel query, and JSON output.
63
64	## Quick Examples
65
66	```python
67	from importlib.machinery import SourceFileLoader
68	mt = SourceFileLoader("mt", "16_NCI_DTP_MolTarget.py").load_module()
69
70	data = mt.load_data()
71
72	# Single drug target
73	print(mt.query(data, "EGFR"))
74
75	# Multiple targets
76	print(mt.query(data, ["TP53", "BRAF", "HER2"]))
77
78	# Cell line molecular profile
79	print(mt.query(data, "MCF7"))
80
81	# JSON for downstream pipeline
82	import json
83	hits = mt.search(data, "EGFR")
84	print(json.dumps(mt.to_json(hits[:5]), indent=2))
85	```
86
87	## Data Source & Download
88
89	- Provider: NCI Developmental Therapeutics Program (DTP)
90	- URL: https://wiki.nci.nih.gov/spaces/NCIDTPdata/pages/155845004/Molecular+Target+Data
91	- File: `WEB_DATA_PROTEIN.TXT` (headerless CSV, comma-delimited)
92	- Local Path: `resources_metadata/dti/Molecular Target Data/WEB_DATA_PROTEIN.TXT`
93	- Format: comma-delimited, 14 columns (see Record Fields above)
94	- Auth: None (public domain, U.S. government)
95
96	### Download Commands
97
98	```bash
99	# File already at:
100	# resources_metadata/dti/Molecular Target Data/WEB_DATA_PROTEIN.TXT
101	```

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