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Julián Candia, Ph.D.

Julián Candia, Ph.D.

  • Center for Cancer Research
  • National Cancer Institute

RESEARCH SUMMARY

Dr. Candia's research interests are focused on the development and application of analysis tools to provide new insight into biological processes relevant to human health. In particular, the availability of high-throughput, multiparametric datasets presents unique opportunities--and challenges--for the development of novel cross-disciplinary tools and frameworks. In this context, his goal is to apply his expertise at the crossroads of bioinformatics, machine learning, network science, and statistical physics to contribute innovative ideas to key problems in biomedical research.

Dr. Candia is currently a Staff Scientist at the Longitudinal Studies Section of the Translational Gerontology Branch at the National Institute on Aging (Baltimore, MD). Previously, he was part of a CCR basic/translational research program aimed at uncovering the molecular underpinnings of liver carcinogenesis and their clinical applications towards personalized cancer medicine.

Areas of Expertise

1) computational biology 2) bioinformatics 3) machine learning 4) systems biology 5) cancer genomics 6) aging 7) data science 8) statistics

Publications

Selected Recent Publications

Serum proteomics links suppression of tumor immunity to ancestry and lethal prostate cancer

Minas TZ*, Candia J*, Dorsey TH, Baker F, Tang W, Kiely M, Smith CJ, Zhang AL, Jordan SV, Obadi OM,
Ajao A, Tettey Y, Biritwum RB, Adjei AA, Mensah JE, Hoover RN, Jenkins FJ, Kittles R, Hsing AW, Wang XW,
Loffredo CA, Yates C, Cook MB, Ambs S
Nature Communications. 13: 1759, 2022. [ Journal Article ]

Assessment of Variability in the Plasma 7k SomaScan Proteomics Assay

Candia J, Daya GN, Tanaka T, Ferrucci L, Walker KA
Scientific Reports. 12: 17147, 2022. [ Journal Article ]

The genomic landscape of Mongolian hepatocellular carcinoma

Candia J, Bayarsaikhan E, Tandon M, Budhu A, Forgues M, Tovuu LO, Tudev U, Lack J, Chao A, Chinburen J, Wang XW
Nature Communications. 11: 4383, 2020. [ Journal Article ]

eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models

Candia J, Tsang JS
BMC Bioinformatics . 20: 189, 2019. [ Journal Article ]

Assessment of variability in the SOMAscan assay

Candia J, Cheung F, Kotliarov Y, Fantoni G, Sellers B, Griesman T, Huang J, Stuccio S, Zingone A, Ryan BM, Tsang JS, Biancotto A.
Scientific Reports. 7: 14248, 2017. [ Journal Article ]