Creating a metabolic pathway in Neo4j

Question

I am attempting to create the glycolytic pathway shown in the image at the bottom of this question, in Neo4j, using these data:

glycolysis_bioentities.csv

name
α-D-glucose
glucose 6-phosphate
fructose 6-phosphate
"fructose 1,6-bisphosphate"
dihydroxyacetone phosphate
D-glyceraldehyde 3-phosphate
"1,3-bisphosphoglycerate"
3-phosphoglycerate
2-phosphoglycerate
phosphoenolpyruvate
pyruvate
hexokinase
glucose-6-phosphatase
phosphoglucose isomerase
phosphofructokinase
"fructose-bisphosphate aldolase, class I"
triosephosphate isomerase (TIM)
glyceraldehyde-3-phosphate dehydrogenase
phosphoglycerate kinase
phosphoglycerate mutase
enolase
pyruvate kinase

glycolysis_relations.csv

source,relation,target
α-D-glucose,substrate_of,hexokinase
hexokinase,yields,glucose 6-phosphate
glucose 6-phosphate,substrate_of,glucose-6-phosphatase
glucose-6-phosphatase,yields,α-D-glucose
glucose 6-phosphate,substrate_of,phosphoglucose isomerase
phosphoglucose isomerase,yields,fructose 6-phosphate
fructose 6-phosphate,substrate_of,phosphofructokinase
phosphofructokinase,yields,"fructose 1,6-bisphosphate"
"fructose 1,6-bisphosphate",substrate_of,"fructose-bisphosphate aldolase, class I"
"fructose-bisphosphate aldolase, class I",yields,D-glyceraldehyde 3-phosphate
D-glyceraldehyde 3-phosphate,substrate_of,glyceraldehyde-3-phosphate dehydrogenase
D-glyceraldehyde 3-phosphate,substrate_of,triosephosphate isomerase (TIM)
triosephosphate isomerase (TIM),yields,dihydroxyacetone phosphate
glyceraldehyde-3-phosphate dehydrogenase,yields,"1,3-bisphosphoglycerate"
"1,3-bisphosphoglycerate",substrate_of,phosphoglycerate kinase
phosphoglycerate kinase,yields,3-phosphoglycerate
3-phosphoglycerate,substrate_of,phosphoglycerate mutase
phosphoglycerate mutase,yields,2-phosphoglycerate
2-phosphoglycerate,substrate_of,enolase
enolase,yields,phosphoenolpyruvate
phosphoenolpyruvate,substrate_of,pyruvate kinase
pyruvate kinase,yields,pyruvate

This is what I have, thus far,

... using this cypher code (passed to Cycli or cypher-shell):

LOAD CSV WITH HEADERS FROM "file:/glycolysis_relations.csv" AS row
MERGE (s:Glycolysis {source: row.source})
MERGE (r:Glycolysis {relation: row.relation})
MERGE (t:Glycolysis {target: row.target})
FOREACH (x in case row.relation when "substrate_of" then [1] else [] end |
  MERGE (s)-[r:substrate_of]->(t)
)
FOREACH (x in case row.relation when "yields" then [1] else [] end |
  MERGE (s)-[r:yields]->(t)
  );

I'd like to create the fully-connected pathway, with captions on all the nodes. Suggestions?

Answer 1

[UPDATED]

There are multiple issues and possible improvements:

1. The second MERGE should be deleted, since it creates orphaned nodes. A relationship type should not be tuned into a Glycolysis node, and such nodes would never be connected to any other nodes.
2. The 1st and 3rd MERGE clauses must use the same property name (say, name) for source and target nodes, or else the same chemical can end up with 2 nodes (with different property keys). This is why you ended up with nodes that did not have all the expected connections.
3. The APOC procedure apoc.cypher.doIt can be used to simplify somewhat the MERGE of relationships with dynamic names.
4. The glycolysis_bioentities.csv is not needed for this use case.

With the above changes, you end up with something like this, which will generate a connected graph that matches your input data:

LOAD CSV WITH HEADERS FROM "file:/glycolysis_relations.csv" AS row
MERGE (s:Glycolysis {name: row.source})
MERGE (t:Glycolysis {name: row.target})
WITH s, t, row
CALL apoc.cypher.doIt(
  'MERGE (s)-[r:' + row.relation + ']->(t)',
  {s:s, t:t}) YIELD value
RETURN 1;