cls.SemanticSimilarity.CSemanticSimilarity Class Reference

Semantic similarity computation. More...

Collaboration diagram for cls.SemanticSimilarity.CSemanticSimilarity:

Public Member Functions
def	__init__ (s, graphInterface)
def	IC (s, goID)
	Get the Information content of a single GOTerm. More...
def	SimResnik (s, goID1, goID2)
	Semantic similarity according to Resnik. More...
def	SimLin (s, goID1, goID2)
	Semantic similarity according to Lin. More...
def	SimIC (s, goID1, goID2)
	Semantic similarity based on Information Coefficient. More...
def	SimGIC (s, goID1, goID2)
	Semantic similarity based on Graph Information Content. More...
def	SimRel (s, goID1, goID2)
	Semantic similarity according to Schlicker et al. More...
def	SimJiangConrath (s, goID1, goID2)
	Semantic similarity according to Jiang and Conrath. More...

Static Public Attributes
string	gfn = "/home/antonia/di-galaxy/data/go/2014-07-ap/bp-2014-07-populated.graphml"
	gi = CGOGraphIGraph();
	sim = CSemanticSimilarity(gi);
	nrNodes = gi.G.vcount();
	i1 = int(random.random()*nrNodes);
	i2 = int(random.random()*nrNodes);
	goIDs = list(sim._Ancs.keys());

Detailed Description

Semantic similarity computation.

Constructor & Destructor Documentation

__init__()

def cls.SemanticSimilarity.CSemanticSimilarity.__init__	(		s,
			graphInterface
	)

Member Function Documentation

IC()

def cls.SemanticSimilarity.CSemanticSimilarity.IC	(		s,
			goID
	)

Get the Information content of a single GOTerm.

    @param goID   GO ID of the term.
    @return @c Float if the value could be computed, else @c None.

SimGIC()

def cls.SemanticSimilarity.CSemanticSimilarity.SimGIC	(		s,
			goID1,
			goID2
	)

Semantic similarity based on Graph Information Content.

    Reference: Pesquita C, Faria D, Bastos H, et al. Metrics for GO based
    protein semantic similarity: a systematic evaluation. BMC
    Bioinformatics 2008;9(Suppl 5):S4.
    Parameters see @ref SimLin.
    @return (@c float) None, if all node in the denominator of the GIC
    formula had @c None values.

SimIC()

def cls.SemanticSimilarity.CSemanticSimilarity.SimIC	(		s,
			goID1,
			goID2
	)

Semantic similarity based on Information Coefficient.

    Reference: Li B, Wang JZ, Feltus FA, et al. Effectively integrating
    information content and structural relationship to improve the
    go-based similarity measure between proteins. Arxiv pre-print
    arXiv:1001.0958 (2010), 1-54. http://arxiv. org/pdf/1001.0958.
    Parameters and return values, see @ref SimLin.

SimJiangConrath()

def cls.SemanticSimilarity.CSemanticSimilarity.SimJiangConrath	(		s,
			goID1,
			goID2
	)

Semantic similarity according to Jiang and Conrath.

    Reference: Jiang JJ, Conrath DW. Semantic similarity based on corpus
    statistics and lexical taxonomy. Arxiv preprint cmp-lg/ 9709008
    (1997), no. Rocling X. In International Conference Research on
    Computational Linguistics (ROCLING X), September 1997, 9008.
    Parameters and return values, see @ref SimLin.

SimLin()

def cls.SemanticSimilarity.CSemanticSimilarity.SimLin	(		s,
			goID1,
			goID2
	)

Semantic similarity according to Lin.

    Reference: Lin D. An information-theoretic definition of
    similarity. In: Proceedings of the 15th International Conference on
    Machine Learning, Vol. 1. 1998, 296-304.
    @param goID1  GO ID of first node.
    @param goID2  GO ID of second node.
    @return @c Float, if the value could be computed. @c None, if either
    the information content of @c goID1's node or @c goID2's node or that
    of the MICA were @c None.

SimRel()

def cls.SemanticSimilarity.CSemanticSimilarity.SimRel	(		s,
			goID1,
			goID2
	)

Semantic similarity according to Schlicker et al.

    Reference: Schlicker A, Domingues FS, Rahnenfuehrer J, et al. A new
    measure for functional similarity of gene products based on Gene
    Ontology. BMC Bioinformatics 2006;7:302.
    Parameters and return values, see @ref SimLin.

SimResnik()

def cls.SemanticSimilarity.CSemanticSimilarity.SimResnik	(		s,
			goID1,
			goID2
	)

Semantic similarity according to Resnik.

    Reference: Resnik P. Using information content to evaluate semantic
    similarity in a taxonomy. Arxiv preprint cmp-lg/9511007 1 (1995). In
    Proceedings of the 14th International Joint Conference on Artificial
    Intelligence IJCAI 95.
    @param goID1  GO ID of first node.
    @param goID2  GO ID of second node.
    @return @c Float if the value could be computed, else @c None.

Member Data Documentation

gfn

string cls.SemanticSimilarity.CSemanticSimilarity.gfn = "/home/antonia/di-galaxy/data/go/2014-07-ap/bp-2014-07-populated.graphml"

static

gi

cls.SemanticSimilarity.CSemanticSimilarity.gi = CGOGraphIGraph();

static

goIDs

cls.SemanticSimilarity.CSemanticSimilarity.goIDs = list(sim._Ancs.keys());

static

i1

cls.SemanticSimilarity.CSemanticSimilarity.i1 = int(random.random()*nrNodes);

static

i2

cls.SemanticSimilarity.CSemanticSimilarity.i2 = int(random.random()*nrNodes);

static

nrNodes

cls.SemanticSimilarity.CSemanticSimilarity.nrNodes = gi.G.vcount();

static

sim

cls.SemanticSimilarity.CSemanticSimilarity.sim = CSemanticSimilarity(gi);

static

---

The documentation for this class was generated from the following file:

• cls/SemanticSimilarity.py