Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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scientific article published on 25 July 2018

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wetenschappelijk artikel

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наукова стаття, опублікована у 2018

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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P1476

Unraveling the bioactivity of anticancer peptides as deduced from machine learning

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P2093

Nalini Schaduangrat

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Watshara Shoombuatong

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P2860

Magainins, a class of antimicrobial peptides from Xenopus skin: isolation, characterization of two active forms, and partial cDNA sequence of a precursor

Studies on anticancer activities of antimicrobial peptides

Roles of d-Amino Acids on the Bioactivity of Host Defense Peptides

Peptides as targeting probes against tumor vasculature for diagnosis and drug delivery

Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012

The future of peptide-based drugs

TumorHoPe: a database of tumor homing peptides

LAMP: A Database Linking Antimicrobial Peptides

Best Practices for QSAR Model Development, Validation, and Exploitation

Identifying anticancer peptides by using improved hybrid compositions

P304

734-752

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P31

scholarly article

P356

10.17179/EXCLI2018-1447

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P407

English

P478

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P50

Chanin Nantasenamat

P577

2018-07-25T00:00:00Z

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P698

30190664

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P921

machine learning

P932

6123611

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