Author

Isha Harshe

Moffitt Cancer Center

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Cancer Biology· 1

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Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1

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Heiko EnderlingiD· 1 shared Renee Brady‐NichollsiD· 1 shared Robert A. GatenbyiD· 1 shared S. PasettoiD· 1 shared

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1 shared paperCancer Biology

Heiko EnderlingORCID

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1 paper

Recent·Most cited

Cancer BiologyBulletin of Mathematical BiologyPeer-reviewedOct 9, 2024

Logistic tumor-population growth and ghost-points symmetry

S. Pasetto, Isha Harshe, Renee Brady‐Nicholls…·Heiko Enderling

This paper introduces a method using logistic function symmetry to estimate tumor growth parameters from limited data, achieving faster and more accurate results than conventional regression approaches.

2 citations

humanstatistical model

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