 Connection
Co-Authors
This is a "connection" page, showing publications co-authored by Farnoush Banaei-Kashani and Russell Bowler.
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Connection Strength |
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0.862 |
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Hill AC, Guo C, Litkowski EM, Manichaikul AW, Yu B, Konigsberg IR, Gorbet BA, Lange LA, Pratte KA, Kechris KJ, DeCamp M, Coors M, Ortega VE, Rich SS, Rotter JI, Gerzsten RE, Clish CB, Curtis JL, Hu X, Obeidat ME, Morris M, Loureiro J, Ngo D, O'Neal WK, Meyers DA, Bleecker ER, Hobbs BD, Cho MH, Banaei-Kashani F, Bowler RP. Large scale proteomic studies create novel privacy considerations. Sci Rep. 2023 06 07; 13(1):9254.
Score: 0.224
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Hussein S, Vu T, Lange L, Bowler RP, Kechris KJ, Banaei-Kashani F. Effective Subject Representation based on Multi-omics Disease Networks using Graph Embedding. Proceedings (IEEE Int Conf Bioinformatics Biomed). 2022 Dec; 2022:1911-1918.
Score: 0.217
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Abdel-Hafiz M, Najafi M, Helmi S, Pratte KA, Zhuang Y, Liu W, Kechris KJ, Bowler RP, Lange L, Banaei-Kashani F. Significant Subgraph Detection in Multi-omics Networks for Disease Pathway Identification. Front Big Data. 2022; 5:894632.
Score: 0.210
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Zhuang Y, Xing F, Ghosh D, Hobbs BD, Hersh CP, Banaei-Kashani F, Bowler RP, Kechris K. Deep learning on graphs for multi-omics classification of COPD. PLoS One. 2023; 18(4):e0284563.
Score: 0.056
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Vu T, Litkowski EM, Liu W, Pratte KA, Lange L, Bowler RP, Banaei-Kashani F, Kechris KJ. NetSHy: network summarization via a hybrid approach leveraging topological properties. Bioinformatics. 2023 01 01; 39(1).
Score: 0.054
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Zhuang Y, Xing F, Ghosh D, Banaei-Kashani F, Bowler RP, Kechris K. An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning. Front Genet. 2021; 12:760299.
Score: 0.051
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Gillenwater LA, Helmi S, Stene E, Pratte KA, Zhuang Y, Schuyler RP, Lange L, Castaldi PJ, Hersh CP, Banaei-Kashani F, Bowler RP, Kechris KJ. Multi-omics subtyping pipeline for chronic obstructive pulmonary disease. PLoS One. 2021; 16(8):e0255337.
Score: 0.050
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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