| Year |
Citation |
Score |
| 2019 |
Amin A, Sanga S, Gan S, Hu Y, Broudy T. Abstract 2472: LOCUS: Queryable database of cancer genomics and pharmacologic response enables rapid selection of in vitro and in vivo preclinical tumor models Cancer Research. 79: 2472-2472. DOI: 10.1158/1538-7445.Sabcs18-2472 |
0.469 |
|
| 2019 |
Amin A, Sanga S, Gan S, Li R, Blewett T, Wang Z, Broudy TB. Abstract B070: LOCUS database enables rapid query and targeted selection of preclinical tumor models based on cancer genomics and pharmacologic response Molecular Cancer Therapeutics. 18. DOI: 10.1158/1535-7163.Targ-19-B070 |
0.469 |
|
| 2015 |
Sanga S, Vladimirova A, Goold RD, Klingler TM. Abstract 4870: GenePool: A cloud-based technology for rapidly data mining large-scale, patient-derived cancer genomic cohorts including The Cancer Genome Atlas Cancer Research. 75: 4870-4870. DOI: 10.1158/1538-7445.Am2015-4870 |
0.338 |
|
| 2014 |
Sanga S, Nair P, Mirsaidi C, Broudy T. Abstract 4279: Rapid biomarker discovery using large-scale, patient-derived cancer genomic cohorts Cancer Research. 74: 4279-4279. DOI: 10.1158/1538-7445.Am2014-4279 |
0.443 |
|
| 2013 |
Broudy T, Sanga S, Ricono J, Trikha M, Mirsaidi C, Praveen KN. Abstract 1138: Rapid validation of a novel kinase target using a large scale genomic database and matched patient derived tumor models. Cancer Research. 73: 1138-1138. DOI: 10.1158/1538-7445.Am2013-1138 |
0.427 |
|
| 2009 |
Sanga S, Broom BM, Cristini V, Edgerton ME. Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family. Bmc Medical Genomics. 2: 59. PMID 19747394 DOI: 10.1186/1755-8794-2-59 |
0.539 |
|
| 2009 |
Sinek JP, Sanga S, Zheng X, Frieboes HB, Ferrari M, Cristini V. Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation. Journal of Mathematical Biology. 58: 485-510. PMID 18781304 DOI: 10.1007/S00285-008-0214-Y |
0.53 |
|
| 2009 |
Edgerton M, Chuang Y, Macklin P, Sanga S, Kim J, Tamaiuolo G, Yang W, Broom A, Do K, Cristini V. Using mathematical models to understand the time dependence of the growth of ductal carcinoma in situ. Cancer Research. 69: 1165. DOI: 10.1158/0008-5472.Sabcs-1165 |
0.558 |
|
| 2009 |
Chen TC, Sanga S, Chou TY, Cristini V, Edgerton ME. Neural network with K-means clustering via PCA for gene expression profile analysis 2009 Wri World Congress On Computer Science and Information Engineering, Csie 2009. 3: 670-673. DOI: 10.1109/CSIE.2009.945 |
0.47 |
|
| 2009 |
Edgerton ME, Chuang Y, Macklin PT, Kim J, Tomaiuolo G, Broom AD, Sanga S, Cristini V. Grap2 and Cyclin-D Interacting Protein (GCIP) Nuclear Expression Is Significantly More Frequent in Triple-Negative Breast Carcinomas (TNBCs) than Other Subtypes of Breast Carcinomas Modern Pathology. 22. DOI: 10.1038/Modpathol.2008.210 |
0.482 |
|
| 2007 |
Sanga S, Frieboes HB, Zheng X, Gatenby R, Bearer EL, Cristini V. Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth. Neuroimage. 37: S120-34. PMID 17629503 DOI: 10.1016/J.Neuroimage.2007.05.043 |
0.571 |
|
| 2007 |
Sinek JP, Frieboes HB, Sivaraman B, Sanga S, Cristini V. Mathematical and Computational Modeling: Towards the Development and Application of Nanodevices for Drug Delivery Nanotechnologies For the Life Sciences. DOI: 10.1002/9783527610419.Ntls0036 |
0.55 |
|
| 2006 |
Sanga S, Sinek JP, Frieboes HB, Ferrari M, Fruehauf JP, Cristini V. Mathematical modeling of cancer progression and response to chemotherapy. Expert Review of Anticancer Therapy. 6: 1361-76. PMID 17069522 DOI: 10.1586/14737140.6.10.1361 |
0.56 |
|
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