Scientific Model Organism Database
主要 5 モデル生物データベース (FlyBase / WormBase / ZFIN / RGD / MGI) を 統合した遺伝子・表現型・疾患モデル横断検索パイプラインを提供する。
When to Use
- •ヒト遺伝子のモデル生物オルソログを検索するとき
- •モデル生物の表現型データを疾患研究に活用するとき
- •遺伝子改変動物モデルの表現型情報を取得するとき
- •複数のモデル生物間で機能保存性を比較するとき
- •IMPC (既存スキル) を補完してラット/魚/ハエ/線虫データが必要なとき
Quick Start
1. MGI (Mouse Genome Informatics) 遺伝子検索
python
import requests
import pandas as pd
MGI_API = "http://www.informatics.jax.org/api"
def search_mgi_gene(query, limit=20):
"""
MGI マウス遺伝子検索。
Parameters:
query: str — 遺伝子名またはシンボル
limit: int — 最大取得数
"""
url = f"{MGI_API}/gene/search"
params = {"query": query, "limit": limit}
resp = requests.get(url, params=params)
resp.raise_for_status()
data = resp.json()
rows = []
for gene in data.get("results", []):
rows.append({
"mgi_id": gene.get("mgiId"),
"symbol": gene.get("symbol"),
"name": gene.get("name"),
"chromosome": gene.get("chromosome"),
"feature_type": gene.get("featureType"),
"organism": "Mus musculus",
})
df = pd.DataFrame(rows[:limit])
print(f"MGI search '{query}': {len(df)} genes")
return df
2. RGD (Rat Genome Database) 遺伝子検索
python
RGD_API = "https://rest.rgd.mcw.edu/rgdws"
def search_rgd_gene(query, species="rat"):
"""
RGD ラット遺伝子検索。
Parameters:
query: str — 遺伝子シンボル
species: str — "rat", "mouse", "human"
"""
species_map = {"rat": 3, "mouse": 2, "human": 1}
species_key = species_map.get(species, 3)
url = f"{RGD_API}/genes/{query}/{species_key}"
resp = requests.get(url, headers={"Accept": "application/json"})
resp.raise_for_status()
data = resp.json()
if isinstance(data, dict):
data = [data]
rows = []
for gene in data:
rows.append({
"rgd_id": gene.get("rgdId"),
"symbol": gene.get("symbol"),
"name": gene.get("name"),
"chromosome": gene.get("chromosome"),
"type": gene.get("type"),
"organism": species,
})
df = pd.DataFrame(rows)
print(f"RGD search '{query}': {len(df)} genes ({species})")
return df
3. ZFIN (Zebrafish Information Network)
python
ZFIN_API = "https://zfin.org/action/api"
def search_zfin_gene(query, limit=20):
"""
ZFIN ゼブラフィッシュ遺伝子検索。
Parameters:
query: str — 遺伝子名またはシンボル
limit: int — 最大取得数
"""
url = f"{ZFIN_API}/marker/search"
params = {"name": query, "limit": limit, "type": "gene"}
resp = requests.get(url, params=params)
resp.raise_for_status()
data = resp.json()
rows = []
for gene in data.get("results", []):
rows.append({
"zfin_id": gene.get("zdbID"),
"symbol": gene.get("abbreviation"),
"name": gene.get("name"),
"type": gene.get("markerType"),
"organism": "Danio rerio",
})
df = pd.DataFrame(rows[:limit])
print(f"ZFIN search '{query}': {len(df)} genes")
return df
4. FlyBase (Drosophila)
python
FLYBASE_API = "https://api.flybase.org/api/v1.0"
def search_flybase_gene(query, limit=20):
"""
FlyBase ショウジョウバエ遺伝子検索。
Parameters:
query: str — 遺伝子名またはシンボル
limit: int — 最大取得数
"""
url = f"{FLYBASE_API}/gene/search/{query}"
params = {"limit": limit}
resp = requests.get(url, params=params)
resp.raise_for_status()
data = resp.json()
genes = data.get("resultset", {}).get("result", [])
rows = []
for gene in genes:
rows.append({
"flybase_id": gene.get("id"),
"symbol": gene.get("symbol"),
"name": gene.get("name"),
"chromosome": gene.get("location", {}).get("chromosome"),
"organism": "Drosophila melanogaster",
})
df = pd.DataFrame(rows[:limit])
print(f"FlyBase search '{query}': {len(df)} genes")
return df
5. WormBase (C. elegans)
python
WORMBASE_API = "https://wormbase.org/rest"
def search_wormbase_gene(query, limit=20):
"""
WormBase 線虫遺伝子検索。
Parameters:
query: str — 遺伝子名またはシンボル
limit: int — 最大取得数
"""
url = f"{WORMBASE_API}/field/gene/{query}/overview"
resp = requests.get(url, headers={"Accept": "application/json"})
resp.raise_for_status()
data = resp.json()
overview = data.get("overview", {})
info = {
"wormbase_id": overview.get("name", {}).get("data", {}).get("id"),
"symbol": overview.get("name", {}).get("data", {}).get("label"),
"concise_description": overview.get("concise_description", {}).get(
"data", ""
),
"organism": "Caenorhabditis elegans",
}
print(f"WormBase: {info['symbol']} ({info['wormbase_id']})")
return info
6. モデル生物横断オルソログ検索
python
def cross_species_ortholog_search(human_gene):
"""
ヒト遺伝子の 5 モデル生物オルソログ横断検索。
Parameters:
human_gene: str — ヒト遺伝子シンボル (例: "TP53")
Pipeline:
MGI → RGD → ZFIN → FlyBase → WormBase
"""
results = []
# Mouse (MGI)
try:
mgi = search_mgi_gene(human_gene, limit=3)
if not mgi.empty:
results.append({"organism": "Mouse", "db": "MGI",
"symbol": mgi.iloc[0]["symbol"],
"id": mgi.iloc[0]["mgi_id"]})
except Exception as e:
print(f"MGI error: {e}")
# Rat (RGD)
try:
rgd = search_rgd_gene(human_gene, "rat")
if not rgd.empty:
results.append({"organism": "Rat", "db": "RGD",
"symbol": rgd.iloc[0]["symbol"],
"id": str(rgd.iloc[0]["rgd_id"])})
except Exception as e:
print(f"RGD error: {e}")
# Zebrafish (ZFIN)
try:
zfin = search_zfin_gene(human_gene.lower(), limit=3)
if not zfin.empty:
results.append({"organism": "Zebrafish", "db": "ZFIN",
"symbol": zfin.iloc[0]["symbol"],
"id": zfin.iloc[0]["zfin_id"]})
except Exception as e:
print(f"ZFIN error: {e}")
# Drosophila (FlyBase)
try:
fly = search_flybase_gene(human_gene, limit=3)
if not fly.empty:
results.append({"organism": "Drosophila", "db": "FlyBase",
"symbol": fly.iloc[0]["symbol"],
"id": fly.iloc[0]["flybase_id"]})
except Exception as e:
print(f"FlyBase error: {e}")
# C. elegans (WormBase)
try:
worm = search_wormbase_gene(human_gene.lower())
if worm.get("wormbase_id"):
results.append({"organism": "C. elegans", "db": "WormBase",
"symbol": worm["symbol"],
"id": worm["wormbase_id"]})
except Exception as e:
print(f"WormBase error: {e}")
df = pd.DataFrame(results)
print(f"\nOrthologs of {human_gene}: {len(df)} model organisms")
return df
7. 表現型データ統合
python
def get_mgi_phenotypes(mgi_id):
"""
MGI 遺伝子の表現型アノテーション取得。
Parameters:
mgi_id: str — MGI ID (例: "MGI:98834")
"""
url = f"{MGI_API}/gene/{mgi_id}/phenotypes"
resp = requests.get(url)
resp.raise_for_status()
data = resp.json()
rows = []
for pheno in data.get("phenotypes", []):
rows.append({
"mp_id": pheno.get("mpId"),
"mp_term": pheno.get("mpTerm"),
"allele_symbol": pheno.get("alleleSymbol"),
"genetic_background": pheno.get("geneticBackground"),
})
df = pd.DataFrame(rows)
print(f"Phenotypes for {mgi_id}: {len(df)} MP annotations")
return df
パイプライン統合
code
ensembl-genomics ──→ model-organism-db ──→ disease-research
(オルソログ ID) (表現型データ) (疾患モデル)
│ │ ↓
biothings-idmapping ──┘ ↓ rare-disease-genetics
(ID マッピング) phylogenetics (OMIM/Orphanet)
(種間系統解析)
パイプライン出力
| ファイル | 説明 | 次スキル |
|---|---|---|
results/model_orthologs.csv | モデル生物オルソログ | → ensembl-genomics |
results/mgi_phenotypes.csv | マウス表現型 | → disease-research |
results/cross_species.json | 横断比較結果 | → phylogenetics |