Entrez 是NCBI提供的在线搜索系统.它通过支持布尔运算符和字段搜索的集成全局查询，提供对几乎所有已知分子生物学数据库的访问.它返回来自所有数据库的结果，其中包含来自每个数据库的命中数，带有指向原始数据库的链接的记录等信息.
可以通过Entrez访问的一些流行数据库列出如下 :
Pubmed
Pubmed Central
核苷酸(GenBank序列数据库)
蛋白质(序列数据库)
基因组(全基因组数据库)
结构(三维大分子结构)
分类学(GenBank中的生物)
SNP(单核苷酸多态性)
UniGene(基因导向的转录序列簇)
CDD(保守蛋白质域数据库)
3D域(来自Entrez结构的域) )
除上述数据库外，Entrez还提供了更多数据库来执行字段搜索.
Biopython提供Entrez特定的模块le，Bio.Entrez访问Entrez数据库.让我们在本章中学习如何使用Biopython访问Entrez :
要添加Entrez的功能，请导入以下模块 :
>>>来自Bio import Entrez
接下来设置您的电子邮件，以确定谁与下面给出的代码相关联;<
>>> Entrez.email ='< youremail>'
然后，设置Entrez工具参数，默认情况下，它是Biopython.
>>> Entrez.tool ='Demoscript'
现在，调用einfo函数查找索引术语计数，上次更新以及每个数据库的可用链接如下定义 :
>>> info = Entrez.einfo()
einfo方法返回一个对象，通过其读取方法提供对信息的访问，如下所示 :
>>> data = info.read() >>> print(data) <?xml version = "1.0" encoding = "UTF-8" ?> <!DOCTYPE eInfoResult PUBLIC "-//NLM//DTD einfo 20130322//EN" "https://img01.yuandaxia.cn/Content/img/tutorials/biopython/einfo.dtd> <eInfoResult> <DbList> <DbName>pubmed</DbName> <DbName>protein</DbName> <DbName>nuccore</DbName> <DbName>ipg</DbName> <DbName>nucleotide</DbName> <DbName>nucgss</DbName> <DbName>nucest</DbName> <DbName>structure</DbName> <DbName>sparcle</DbName> <DbName>genome</DbName> <DbName>annotinfo</DbName> <DbName>assembly</DbName> <DbName>bioproject</DbName> <DbName>biosample</DbName> <DbName>blastdbinfo</DbName> <DbName>books</DbName> <DbName>cdd</DbName> <DbName>clinvar</DbName> <DbName>clone</DbName> <DbName>gap</DbName> <DbName>gapplus</DbName> <DbName>grasp</DbName> <DbName>dbvar</DbName> <DbName>gene</DbName> <DbName>gds</DbName> <DbName>geoprofiles</DbName> <DbName>homologene</DbName> <DbName>medgen</DbName> <DbName>mesh</DbName> <DbName>ncbisearch</DbName> <DbName>nlmcatalog</DbName> <DbName>omim</DbName> <DbName>orgtrack</DbName> <DbName>pmc</DbName> <DbName>popset</DbName> <DbName>probe</DbName> <DbName>proteinclusters</DbName> <DbName>pcassay</DbName> <DbName>biosystems</DbName> <DbName>pccompound</DbName> <DbName>pcsubstance</DbName> <DbName>pubmedhealth</DbName> <DbName>seqannot</DbName> <DbName>snp</DbName> <DbName>sra</DbName> <DbName>taxonomy</DbName> <DbName>biocollections</DbName> <DbName>unigene</DbName> <DbName>gencoll</DbName> <DbName>gtr</DbName> </DbList> </eInfoResult>
数据采用XML格式，要将数据作为python对象获取，请尽快使用 Entrez.read 方法调用Entrez.einfo()方法 :
>>> info = Entrez.einfo() >>> record = Entrez.read(info)
这里，record是一个字典，它有一个键，DbList如下所示 :
>>> record.keys() [u'DbList']
访问DbList键返回下面显示的数据库名称列表 :
>>> record[u'DbList'] ['pubmed', 'protein', 'nuccore', 'ipg', 'nucleotide', 'nucgss', 'nucest', 'structure', 'sparcle', 'genome', 'annotinfo', 'assembly', 'bioproject', 'biosample', 'blastdbinfo', 'books', 'cdd', 'clinvar', 'clone', 'gap', 'gapplus', 'grasp', 'dbvar', 'gene', 'gds', 'geoprofiles', 'homologene', 'medgen', 'mesh', 'ncbisearch', 'nlmcatalog', 'omim', 'orgtrack', 'pmc', 'popset', 'probe', 'proteinclusters', 'pcassay', 'biosystems', 'pccompound', 'pcsubstance', 'pubmedhealth', 'seqannot', 'snp', 'sra', 'taxonomy', 'biocollections', 'unigene', 'gencoll', 'gtr'] >>>
基本上，Entrez模块解析Entrez搜索系统返回的XML并将其作为python词典和列表提供.
要搜索Entrez数据库中的任何一个，我们可以使用Bio.Entrez.esearch()模块.它的定义低于 :
>>> info = Entrez.einfo()
>>> info = Entrez.esearch(db = "pubmed",term = "genome")
>>> record = Entrez.read(info)
>>>print(record)
DictElement({u'Count': '1146113', u'RetMax': '20', u'IdList':
['30347444', '30347404', '30347317', '30347292',
'30347286', '30347249', '30347194', '30347187',
'30347172', '30347088', '30347075', '30346992',
'30346990', '30346982', '30346980', '30346969',
'30346962', '30346954', '30346941', '30346939'],
u'TranslationStack': [DictElement({u'Count':
'927819', u'Field': 'MeSH Terms', u'Term': '"genome"[MeSH Terms]',
u'Explode': 'Y'}, attributes = {})
, DictElement({u'Count': '422712', u'Field':
'All Fields', u'Term': '"genome"[All Fields]', u'Explode': 'N'}, attributes = {}),
'OR', 'GROUP'], u'TranslationSet': [DictElement({u'To': '"genome"[MeSH Terms]
OR "genome"[All Fields]', u'From': 'genome'}, attributes = {})], u'RetStart': '0',
u'QueryTranslation': '"genome"[MeSH Terms] OR "genome"[All Fields]'},
attributes = {})
>>>如果您指定了错误的数据库，则返回
>>> info = Entrez.esearch(db = "blastdbinfo",term = "books")
>>> record = Entrez.read(info)
>>> print(record)
DictElement({u'Count': '0', u'RetMax': '0', u'IdList': [],
u'WarningList': DictElement({u'OutputMessage': ['No items found.'],
u'PhraseIgnored': [], u'QuotedPhraseNotFound': []}, attributes = {}),
u'ErrorList': DictElement({u'FieldNotFound': [], u'PhraseNotFound':
['books']}, attributes = {}), u'TranslationSet': [], u'RetStart': '0',
u'QueryTranslation': '(books[All Fields])'}, attributes = {})如果要跨数据库搜索，然后你可以使用 Entrez.egquery .这类似于 Entrez.esearch ，但它足以指定关键字并跳过数据库参数.
>>>info = Entrez.egquery(term = "entrez") >>> record = Entrez.read(info) >>> for row in record["eGQueryResult"]: ... print(row["DbName"], row["Count"]) ... pubmed 458 pmc 12779 mesh 1 ... ... ... biosample 7 biocollections 0
Enterz提供了一种特殊方法，用于搜索和下载Entrez记录的完整详细信息.请考虑以下简单示例 :
>>> handle = Entrez.efetch( db ="nucleotide"，id ="EU490707"，rettype ="fasta")
现在，我们可以只需使用SeqIO对象读取记录
>>> record = SeqIO.read( handle, "fasta" )
>>> record
SeqRecord(seq = Seq('ATTTTTTACGAACCTGTGGAAATTTTTGGTTATGACAATAAATCTAGTTTAGTA...GAA',
SingleLetterAlphabet()), id = 'EU490707.1', name = 'EU490707.1',
description = 'EU490707.1
Selenipedium aequinoctiale maturase K (matK) gene, partial cds; chloroplast',
dbxrefs = [])
