Grey, S R <br/><br/>
Prediction of nodal spread of breast cancer by using artificial neural network-based analyses of S100A4, nm23 and steroid receptor expression.  [electronic resource] 

 -  Clinical & experimental metastasis  2003 
 - 507-14 p.  digital 
<br/><br/> Publication Type: Journal Article 
<br/><br/><label>ISSN: </label>0262-0898 
<br/><br/><label>Standard No.: </label>10.1023/a:1025846019656  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Adult<br/>Aged<br/>Aged, 80 and over<br/>Breast Neoplasms--pathology<br/>Female<br/>Gene Expression Regulation, Neoplastic<br/>Genes, Tumor Suppressor<br/>Genetic Markers<br/>Humans<br/>Lymphatic Metastasis--pathology<br/>Middle Aged<br/>Models, Theoretical<br/>Monomeric GTP-Binding Proteins--genetics<br/>NM23 Nucleoside Diphosphate Kinases<br/>Nerve Net<br/>Nucleoside-Diphosphate Kinase<br/>Predictive Value of Tests<br/>Promoter Regions, Genetic<br/>Receptors, Estrogen--genetics<br/>Receptors, Progesterone--genetics<br/>Receptors, Steroid--genetics<br/>S100 Calcium-Binding Protein A4<br/>S100 Proteins--genetics<br/>Transcription Factors--genetics