Projects: bioconductor: GraphPAC
https://packages.ecosyste.ms/registries/bioconductor.org/packages/GraphPAC
Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach.
1 version
Latest release: over 2 years ago
1 dependent package
18,848 downloads total
Science Score: 98/100
Starting Score: 100 points
Bonuses:
-
+8
Academic maintainer emails
1 maintainers with academic email addresses
Penalties:
-
-10
No science terms in description
No scientific terms found in description
Very Likely Science (98)
Papers Mentioning GraphPAC 5
10.1016/j.cels.2020.06.005
PertInInt: An Integrative, Analytical Approach to Rapidly Uncover Cancer Driver Genes with Perturbed Interactions and FunctionalitiesCited by: 7
Author(s): Shilpa Nadimpalli Kobren, Bernard Chazelle, Mona Singh
Software Mentions: 5
Published: almost 6 years ago
10.1186/s12859-016-0963-3
Leveraging protein quaternary structure to identify oncogenic driver mutationsCited by: 8
Author(s): Gregory A. Ryslik, Yu‐Wei Cheng, Yorgo Modis, Hongyu Zhao
Software Mentions: 4
Published: about 10 years ago
10.1186/s13073-014-0081-7
Functional consequences of somatic mutations in cancer using protein pocket-based prioritization approachCited by: 31
Author(s): Huy Gia Vuong, Feixiong Cheng, Lin Chen, Zhongming Zhao
Software Mentions: 4
Published: over 11 years ago
10.1186/1471-2105-15-231
A spatial simulation approach to account for protein structure when identifying non-random somatic mutationsCited by: 23
Author(s): Gregory A. Ryslik, Yu‐Wei Cheng, Kei Hoi Cheung, Robert Bjornson, Daniel Zelterman, Yorgo Modis, Hongyu Zhao
Software Mentions: 3
Published: almost 12 years ago
10.1186/1471-2105-15-86
A graph theoretic approach to utilizing protein structure to identify non-random somatic mutationsCited by: 29
Author(s): Gregory A. Ryslik, Yu‐Wei Cheng, Kei Hoi Cheung, Yorgo Modis, Hongyu Zhao
Software Mentions: 2
Published: about 12 years ago