Juan Manuel Dominguez

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Assistant Professor

Universidad Francisco de Vitoria

Spain

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About

Juan Manuel Dominguez is an Assistant Professor at Universidad Francisco de Vitoria, Spain. His research encompasses the development of predictive models in oncology, machine learning applications for genetic data, and innovative approaches to targeting tumors with antibody-drug conjugates. Recent publications include studies on KRAS wild type colorectal cancer, prostate cancer mortality prediction, and the role of genes in non-small cell lung cancer.

Recent Grants

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Descubrimiento de antitumorales innovadores dirigidos contra dianas oncológicas: sistema topoisomerasa y regulación de la respuesta inmune - INMUNOTOP

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Desarrollo de una nueva generación de terapias anticáncer: Conjugados de anticuerpos a fármacos marinos - MARINMAB

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Modulación de alfa-secretasa mediante compuestos marinos en el tratamiento del Alzheimer.

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Soluciones innovadoras para acelerar la identificación y desarrollo de fármacos en patologías del sistema nervioso - DENDRIA

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Caracterización de compuestos de origen marino y sus derivados con capacidad neuroprotectora para el tratamiento de enfermedades neurodegenerativas

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Articles (13)

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2025

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2024

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2024

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2024

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2024

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2022

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2022

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2022

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2021

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2020

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2020

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2020

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2020

Collaborators (1)

Juan Manuel Zapata Hernández

Tenured scientist/head of Department

Consejo Superior de Investigaciones Cientificas

SPAIN

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Juan Manuel Dominguez

Research Interests

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About

Recent Grants

Articles (13)

PROCC: a predictive score to identify KRAS wild type metastatic colorectal cancer patients who are likely to obtain survival benefit from panitumumab treatment.

Development and validation of MOSPROC, an easily applicable predictive score of mortality for patients with prostate cancer

GFPrint™: A MACHINE LEARNING TOOL FOR TRANSFORMING GENETIC DATA INTO CLINICAL INSIGHTS

Identification of genes related to PD-L1 expression in non-small cell lung cancer (NSCLC) tumor samples by GFPrint, a machine learning framework (MLF)

GFPrint™: A machine learning tool for transforming genetic data into clinical insights

A deep learning framework (DLF) to identify clinical predictors of disease progression and mortality in metastatic castration-resistant prostate cancer (mCRPC) patients treated with docetaxel/prednisone (DP).

Development and validation of a predictive score to identify K-Ras wild-type (WT) metastatic colorectal cancer (mCRC) patients who are likely to benefit from Panitumumab (P) treatment.

Profiling of clinically relevant subgroups of asymptomatic or mild-symptomatic metastatic castration-resistant prostate cancer (mCRPC) patients using PSA and testosterone levels and deep learning.

Structural Cues for Understanding eEF1A2 Moonlighting

CD13 as a new tumor target for antibody-drug conjugates: validation with the conjugate MI130110

From Ugi Multicomponent Reaction to Linkers for Bioconjugation

Structural cues for understanding eEF1A2 moonlighting.

CD13 as a new tumor target for antibody-drug conjugates: validation with the conjugate MI130110

Collaborators (1)

Juan Manuel Zapata Hernández

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