Related Work

Flags and Lollipops Open Lab Notebook

Alison Meynarts MSc Research

  • Used GeneRIFs, gene2pubmed, Swissprot PubMed Links

Combining P-values (Fisher's Method derivation by Lou Jost)

Also investigate TOPPGENE

  • Use Mammalian Phenotype Ontology (this has links to mouse genes?)
  • Assume orthologous genes implies similar phenotype
  • use co-occurrence of genes in PMID via gene2pubmed as implying gene interaction
  • Compared to SUSPECTS and ENDEAVOR
  • Used "information content" - occurrences of term and children vs all terms
  • Uses Sugeno "Fuzzy Measure"
  • Should see if I can extract validation set from supplementary files

Also extract algorithms covered in Proposal

Links to Related Gene Prioritization Algorithms

(courtesy of Gary Bader)

Association of genes to genetically inherited diseases using data mining.

G2D (See proposal)

The human disease network.

Analysis of human disease network obtained from OMIM.

A human phenome-interactome network of protein complexes implicated in
genetic disorders.

Interactome-Phenome network. Assume mutations in interaction partners causing phenotype can be projected to interaction partners.

Gene prioritization through genomic data fusion.
*this one comes with software called Endeavour, which claims to be easy
to use*

Endeavor, information fusion for gene prioritisation.

A computational system to select candidate genes for complex human traits

CAESAR system

Genome-wide identification of genes likely to be involved in human
genetic disease

Prediction from sequence properties

Discovering disease-genes by topological features in human
protein–protein interaction network

PPI to build KNN classifier for prediction (print and read!)

Analysis of protein sequence and interaction data for candidate disease
gene prediction
Computational disease gene identification: a concert of methods
prioritizes type 2 diabetes and obesity candidate genes

Multiple methods applied to the same problem

SUSPECTS: enabling fast and effective prioritization of positional
Target SNP selection in complex disease association studies
POCUS: mining genomic sequence annotation to predict disease genes

Comparative Toxicogenomics Database

  • Database of curated/inferred chemical/gene/disease/pathway interactions (pairwise)
  • Entrez/Unigene, OMIM, KEGG, MeSH
  • Inference via transitivity (chem-gene + gene-disease = chem-disease)

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

  • Trad. Chinese Medicine/gene/disease, using MeSH terms for disease.
  • Transitivity (Swanson ABC) - our profile score is like doing the Swanson ABC en masse.
  • PharmGKB (gene/disease/outcome database) - stores disease outcomes preferably as MeSH terms

GeneCards Disease Genes List

Gene to Expression Data (with MeSH term annotation)

GeneMeSH does hypergeometric probability linking of Genes-to-MeSH via gene2pubmed

GenoMeSH ( He Group)

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