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Link prediction using Heat Diffusion Approach in STRING and BIOGRID data
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Readme
adamic_adar_baseline.py
baseline_methods.py
coexp_scores.txt
combined_scores.txt
cooccurence_scores.txt
database_scores.txt
experimental_scores.txt
fusion_scores.txt
heat_diffusion_on_biogrid_data.py
heat_diffusion_on_string_data.py
neighborhood_scores.txt
page_rank_katz.py
physical_interaction_gene.txt
textmining_scores.txt
tumor_interaction_gene.txt

Readme

for STRING data heat diffusion link prediction run: heat_diffusion_on_string_data.py
for BioGRID data heat diffusion link prediction run: heat_diffusion_on_biogrid_data.py
for katz_centrality and personalized pageRank run: page_ran_katz.py 

for adamic_adar_link_prediction/resource_allocation link prediction run: adamic_adar_baseline.py and change the function name in scores = resource_allocation_index(TG,gen,tumor_gene_relation_copy)

for nearest neighbor and jaccard similarity run: baseline_methods.py

Data:
physical_interaction_gene.txt ==> BioGrID data
fusion_scores.txt ==> STRING Fusion channel data
coexp_score.txt ===> STRING coexpression channel data
cooccurence_scores.txt ===> STRING cooccurence channel data
combined_scores.txt ===> STRING combined channel data
databse_scores.txt ===> STRING database channel data
experimental_scores.txt ===> STRING experimental channel data
textmining_scores.txt ===> STRING textmining channel data
neighborhood_scores.txt ===> STRING neighborhood channel data

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