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Connection

Nese Kurt Yilmaz to Machine Learning

This is a "connection" page, showing publications Nese Kurt Yilmaz has written about Machine Learning.
Connection Strength

0.384
  1. Leidner F, Kurt Yilmaz N, Schiffer CA. Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning. J Chem Theory Comput. 2021 Apr 13; 17(4):2054-2064.
    View in: PubMed
    Score: 0.160
  2. Leidner F, Kurt Yilmaz N, Schiffer CA. Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints. J Chem Inf Model. 2019 09 23; 59(9):3679-3691.
    View in: PubMed
    Score: 0.143
  3. Leidner F, Kurt Yilmaz N, Schiffer CA. Deciphering Antifungal Drug Resistance in Pneumocystis jirovecii DHFR with Molecular Dynamics and Machine Learning. J Chem Inf Model. 2021 06 28; 61(6):2537-2541.
    View in: PubMed
    Score: 0.041
  4. Matthew AN, Leidner F, Lockbaum GJ, Henes M, Zephyr J, Hou S, Rao DN, Timm J, Rusere LN, Ragland DA, Paulsen JL, Prachanronarong K, Soumana DI, Nalivaika EA, Kurt Yilmaz N, Ali A, Schiffer CA. Drug Design Strategies to Avoid Resistance in Direct-Acting Antivirals and Beyond. Chem Rev. 2021 03 24; 121(6):3238-3270.
    View in: PubMed
    Score: 0.039
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.