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Person Details: Adam T. Szafran

Superfund Research Program

Adam T. Szafran

Baylor College of Medicine
One Baylor Plaza
Cullen Rm. 125A
Houston, Texas 77030-0000
Phone: 713-798-5589






  • Stossi F, Singh PK, Mistry R, Johnson H, Dandekar RD, Mancini MG, Szafran AT, Rao A, Mancini MA. 2022. Quality control for single cell imaging analytics using endocrine disruptor-induced changes in estrogen receptor expression. Environ Health Perspect 130(2):27008. doi:10.1289/EHP9297 PMID:35167326 PMCID:PMC8846386
  • Szafran AT, Mancini MG, Stossi F, Mancini MA. 2022. Sensitive image-based chromatin binding assays using inducible ER-alpha to rapidly characterize estrogenic chemicals and mixtures. iScience 25(10):105200. doi:10.1016/j.isci.2022.105200 PMID:36238893 PMCID:PMC9550643



  • Mukherjee R, Beykal B, Szafran AT, Onel M, Stossi F, Mancini MG, Lloyd D, Wright FA, Zhou L, Mancini MA, Pistikopoulos EN. 2020. Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms. PLoS Comput Biol 16:24. doi:10.1371/journal.pcbi.1008191 PMID:32970665 PMCID:PMC7538107
  • Stossi F, Mistry R, Singh PK, Johnson H, Mancini MG, Szafran AT, Mancini MA. 2020. Single cell distribution analysis of AR levels by high throughput microscopy in cell models: Application for testing endocrine disrupting chemicals. SLAS Discov 11:doi:10.1177/2472555220934420 PMID:32552291
  • Szafran AT, Bolt MJ, Obkirchner CE, Mancini MG, Helsen C, Claessens F, Stossi F, Mancini MA. 2020. A mechanistic high-content analysis assay using a chimeric androgen receptor that rapidly characterizes androgenic chemicals. SLAS Discov 14:doi:10.1177/2472555220922917 PMID:32392092


  • Kuthurua S, Szafran AT, Stossi F, Mancini MA, Rao A. 2019. Leveraging image-derived phenotypic measurements for drug-target interaction predictions. Cancer Inform doi:10.1177/1176935119856595 PMID:31217689 PMCID:PMC6563400
  • Mukherjee R, Onel M, Beykal B, Szafran AT, Stossi F, Mancini MA, Zhou L, Wright FA, Pistikopoulos EN. 2019. Development of the Texas A&M Superfund Research Program computational platform for data integration, visualization, and analysis. Computer Aided Chemical Engineering 46:967-972. doi:10.1016/B978-0-12-818634-3.50162-4 PMID:31612156 PMCID:PMC6791821
  • Xia J, Chiu L, Nehring R, Bravo Nunez M, Mei Q, Perez M, Zhai Y, Fitzgerald D, Pribis J, Wang Y, Hu C, Powell R, LaBonte S, Jalali A, Matadamas Guzman M, Lentzsch A, Szafran AT, Joshi M, Richters M, Gibson J, Frisch R, Hastings P, Bates D, Queitsch C, Hilsenbeck SG, Coarfa C, Hu JC, Siegele DA, Scott KL, Liang H, Mancini MA, Herman C, Miller KM, Rosenberg SM. 2019. Bacteria-to-human protein networks reveal origins of endogenous DNA damage. Cell 176(1-2):127-143. doi:10.1016/j.cell.2018.12.008 PMID:30633903 PMCID:PMC6344048


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