scholarly journals Peer Review #2 of "Finding melanoma drugs through a probabilistic knowledge graph (v0.1)"

2017 ◽  
Keyword(s):  
Peer Review ◽  
Knowledge Graph ◽  
Probabilistic Knowledge

scholarly journals Finding melanoma drugs through a probabilistic knowledge graph

2016 ◽  
Author(s):  
James P McCusker ◽  
Michel Dumontier ◽  
Rui Yan ◽  
Sylvia He ◽  
Jonathan S Dordick ◽  
...  
Keyword(s):  
Systems Biology ◽  
Probabilistic Methods ◽  
Drug Candidate ◽  
Knowledge Graph ◽  
Web Interface ◽  
Drug Candidates ◽  
Probabilistic Knowledge ◽  
Data Explosion

Metastatic cutaneous melanoma is an aggressive skin cancer with some progression-slowing treatments but no known cure. The omics data explosion has created many possible drug candidates, however filtering criteria remain challenging, and systems biology approaches have become fragmented with many disconnected databases. Using drug, protein, and disease interactions, we built an evidence-weighted knowledge graph of integrated interactions. Our knowledge graph-based system, ReDrugS, can be used via an API or web interface, and has generated 25 high quality melanoma drug candidates. We show that probabilistic analysis of systems biology graphs increases drug candidate quality compared to non-probabilistic methods. Four of the 25 candidates are novel therapies, three of which have been tested with other cancers. All other candidates have current or completed clinical trials, or have been studied in in vivo or in vitro. This approach can be used to identify candidate therapies for use in research or personalized medicine.

scholarly journals Finding melanoma drugs through a probabilistic knowledge graph

2016 ◽  
Author(s):  
James P McCusker ◽  
Michel Dumontier ◽  
Rui Yan ◽  
Sylvia He ◽  
Jonathan S Dordick ◽  
...  
Keyword(s):  
Systems Biology ◽  
Probabilistic Methods ◽  
Drug Candidate ◽  
Knowledge Graph ◽  
Web Interface ◽  
Drug Candidates ◽  
Probabilistic Knowledge ◽  
Data Explosion

Metastatic cutaneous melanoma is an aggressive skin cancer with some progression-slowing treatments but no known cure. The omics data explosion has created many possible drug candidates, however filtering criteria remain challenging, and systems biology approaches have become fragmented with many disconnected databases. Using drug, protein, and disease interactions, we built an evidence-weighted knowledge graph of integrated interactions. Our knowledge graph-based system, ReDrugS, can be used via an API or web interface, and has generated 25 high quality melanoma drug candidates. We show that probabilistic analysis of systems biology graphs increases drug candidate quality compared to non-probabilistic methods. Four of the 25 candidates are novel therapies, three of which have been tested with other cancers. All other candidates have current or completed clinical trials, or have been studied in in vivo or in vitro. This approach can be used to identify candidate therapies for use in research or personalized medicine.

scholarly journals Finding melanoma drugs through a probabilistic knowledge graph

2016 ◽  
Author(s):  
James P McCusker ◽  
Michel Dumontier ◽  
Rui Yan ◽  
Sylvia He ◽  
Jonathan S Dordick ◽  
...  
Keyword(s):  
Systems Biology ◽  
Probabilistic Methods ◽  
Drug Candidate ◽  
Knowledge Graph ◽  
Web Interface ◽  
Drug Candidates ◽  
Probabilistic Knowledge ◽  
Data Explosion

Metastatic cutaneous melanoma is an aggressive skin cancer with some progression-slowing treatments but no known cure. The omics data explosion has created many possible drug candidates, however filtering criteria remain challenging, and systems biology approaches have become fragmented with many disconnected databases. Using drug, protein, and disease interactions, we built an evidence-weighted knowledge graph of integrated interactions. Our knowledge graph-based system, ReDrugS, can be used via an API or web interface, and has generated 25 high quality melanoma drug candidates. We show that probabilistic analysis of systems biology graphs increases drug candidate quality compared to non-probabilistic methods. Four of the 25 candidates are novel therapies, three of which have been tested with other cancers. All other candidates have current or completed clinical trials, or have been studied in in vivo or in vitro. This approach can be used to identify candidate therapies for use in research or personalized medicine.

Peer review of a dental curriculum: how one school did it

1976 ◽  
Vol 40 (11) ◽  
pp. 761-762
Author(s):  
PK Morse ◽  
TR Dirksen
Keyword(s):  
Peer Review ◽  
Dental Curriculum
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