python - 如何从其他格式(例如graphml)导出sbml文件？

Question

因此，正如前面提到的，我正在尝试找到一种将 graphml 文件(或其他格式，如 xgmml、csv、edgelist)从 networkx 或 igraph(python 或 R)转换为 SBML 的方法。格式。

我相信应该有一种简单的方法，但是......我找不到。有什么想法吗？

编辑:有一些other fomats可以用来最终登陆 SBML 星球，但我仍然不知道如何导出到其中任何一个。

编辑二:here我发布了一个与 SBML 和 Cytoscape 相关的问题，所以...可能对其他对该主题感兴趣的人有用。

Answer 1

SBML主要是基于编码过程或 react 的模型。此类模型的相应网络图是二分图，即图中有两类节点( react 和物种)，并且物种和 react 节点之间只有边，但物种-物种或物种- react 之间没有边。 SBML 中的一个重要概念是 react 中的化学计量，它基本上是定义物种在相应 react 中如何发生的边缘属性。

因此，对于可转换为 SBML 的图，它们必须遵循一定的结构，即它们必须是二部有向图，具有反应和物种节点，边缘上具有化学计量信息。

使用 libsbml 或 JSBML(这两个库都用于操作 SBML)，可以轻松地将此类图转换为 SBML。 我在下面附加了一个示例，其中包含 libsbml 中的 python 绑定(bind)。

"""
Converts simple bipartite species-reaction graph to SBML
using python bindings in libsbml

requirements:
    pip install python-libsbml networkx
"""
import networkx as nx
import libsbml

'''
Create bipartite networkx graph consisting of species and reaction nodes.
Edges require stoichiometry (or set to 1 otherwise).
'''
G = nx.DiGraph()

# add species nodes
G.add_node("S1", ntype="specie")
G.add_node("S2", ntype="specie")
G.add_node("S3", ntype="specie")
G.add_node("S4", ntype="specie")
G.add_node("S5", ntype="specie")
G.add_node("S6", ntype="specie")

# add reaction nodes (and reaction edges)
G.add_node("r1", ntype="reaction")  # 2 S1 -> S2
G.add_edges_from([
    ("S1", "r1", {'stoichiometry': 2}),
    ("r1", "S2", {'stoichiometry': 1})])
G.add_node("r2", ntype="reaction")  # S2 -> S3
G.add_edges_from([
    ("S2", "r2", {'stoichiometry': 1}),
    ("r2", "S3", {'stoichiometry': 1})])
G.add_node("r3", ntype="reaction")  # S3 + S4 -> S5 + S6
G.add_edges_from([
    ("S3", "r3", {'stoichiometry': 1}),
    ("S4", "r3", {'stoichiometry': 1}),
    ("r3", "S5", {'stoichiometry': 1}),
    ("r3", "S6", {'stoichiometry': 1})
])

print(G)
for sid, n in G.nodes.items():
    print(sid, n)
for sid, e in G.edges.items():
    print(sid, e)

'''
Create SBML model from the graph
'''
doc = libsbml.SBMLDocument()  # type: libsbml.SBMLDocument
model = doc.createModel()  # type: libsbml.Model
model.setId("graph_model")
# create species
for sid, n in G.nodes.items():
    print(sid, n)
    if n['ntype'] == "specie":
        s = model.createSpecies()  # type: libsbml.Species
        s.setId(sid)

# create reactions
for sid, n in G.nodes.items():
    if n['ntype'] == "reaction":
        r = model.createReaction()  # type: libsbml.Reaction
        r.setId(sid)
        for reactant_id in G.predecessors(sid):

            stoichiometry = G.edges[reactant_id, sid]['stoichiometry']
            reactant = model.getSpecies(reactant_id)
            r.addReactant(reactant, stoichiometry)

        for product_id in G.successors(sid):
            product = model.getSpecies(product_id)
            stoichiometry = G.edges[sid, product_id]['stoichiometry']
            r.addProduct(product, stoichiometry)

# serialization
sbml_str = libsbml.writeSBMLToString(doc)
print("-" * 80)
print(sbml_str)
libsbml.writeSBMLToFile(doc, "graph2sbml.xml")

与输出

S1 {'ntype': 'specie'}
S2 {'ntype': 'specie'}
S3 {'ntype': 'specie'}
S4 {'ntype': 'specie'}
S5 {'ntype': 'specie'}
S6 {'ntype': 'specie'}
r1 {'ntype': 'reaction'}
r2 {'ntype': 'reaction'}
r3 {'ntype': 'reaction'}
('S1', 'r1') {'stoichiometry': 2}
('S2', 'r2') {'stoichiometry': 1}
('S3', 'r3') {'stoichiometry': 1}
('S4', 'r3') {'stoichiometry': 1}
('r1', 'S2') {'stoichiometry': 1}
('r2', 'S3') {'stoichiometry': 1}
('r3', 'S5') {'stoichiometry': 1}
('r3', 'S6') {'stoichiometry': 1}
S1 {'ntype': 'specie'}
S2 {'ntype': 'specie'}
S3 {'ntype': 'specie'}
S4 {'ntype': 'specie'}
S5 {'ntype': 'specie'}
S6 {'ntype': 'specie'}
r1 {'ntype': 'reaction'}
r2 {'ntype': 'reaction'}
r3 {'ntype': 'reaction'}
--------------------------------------------------------------------------------
<?xml version="1.0" encoding="UTF-8"?>
<sbml xmlns="http://www.sbml.org/sbml/level3/version2/core" level="3" version="2">
  <model id="graph_model">
    <listOfSpecies>
      <species id="S1"/>
      <species id="S2"/>
      <species id="S3"/>
      <species id="S4"/>
      <species id="S5"/>
      <species id="S6"/>
    </listOfSpecies>
    <listOfReactions>
      <reaction id="r1">
        <listOfReactants>
          <speciesReference species="S1" stoichiometry="2" constant="true"/>
        </listOfReactants>
        <listOfProducts>
          <speciesReference species="S2" stoichiometry="1" constant="true"/>
        </listOfProducts>
      </reaction>
      <reaction id="r2">
        <listOfReactants>
          <speciesReference species="S2" stoichiometry="1" constant="true"/>
        </listOfReactants>
        <listOfProducts>
          <speciesReference species="S3" stoichiometry="1" constant="true"/>
        </listOfProducts>
      </reaction>
      <reaction id="r3">
        <listOfReactants>
          <speciesReference species="S3" stoichiometry="1" constant="true"/>
          <speciesReference species="S4" stoichiometry="1" constant="true"/>
        </listOfReactants>
        <listOfProducts>
          <speciesReference species="S5" stoichiometry="1" constant="true"/>
          <speciesReference species="S6" stoichiometry="1" constant="true"/>
        </listOfProducts>
      </reaction>
    </listOfReactions>
  </model>
</sbml>

然后可以使用 Cytoscape 中的 cy3sbml 等工具将 SBML 可视化