Sökning: "rough sets"

Visar resultat 11 - 15 av 25 avhandlingar innehållade orden rough sets.

  1. 11. From Physicochemical Features to Interdependency Networks : A Monte Carlo Approach to Modeling HIV-1 Resistome and Post-translational Modifications

    Författare :Marcin Kierczak; Jan Komorowski; Anna Tramontano; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; bioinformatics; HIV-1; resistome analysis; drug resistance; predicting PTMs; molecular interdependency networks; MCFS-ID; feature selection; interactome; machine-learning; rough sets; Bioinformatics; Bioinformatik; Computer Science; datavetenskap; Biology; with specialization in structural biology; biologi; med inriktning mot strukturbiologi;

    Sammanfattning : The availability of new technologies supplied life scientists with large amounts of experimental data. The data sets are large not only in terms of the number of observations, but also in terms of the number of recorded features. LÄS MER

  3. 12. Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach : Applications for Drug Discovery and Development

    Författare :Aleksejs Kontijevskis; Jarl Wikberg; Jan Komorowski; Robert Glen; Uppsala universitet; []
    Nyckelord :Bioinformatics; proteochemometrics; bioinformatics; chemoinformatics; chemical space; QSAR; retroviral proteases; HIV-1; drug resistance; pharmacogenomics; cytochrome P450; GPCRs; melanocortin receptors; interactome; machine-learning; rough sets; Bioinformatik;

    Sammanfattning : Molecular interactions lie at the heart of myriad biological processes. Knowledge of molecular recognition processes and the ability to model and predict interactions of any biological molecule to any chemical compound are the key for better understanding of cell functions and discovery of more efficacious medicines. LÄS MER

  4. 13. Predictive Healthcare : Cervical Cancer Screening Risk Stratification and Genetic Disease Markers

    Författare :Nicholas Baltzer; Jan Komorowski; Mark Jit; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bioinformatics; Cervical Cancer; Screening; Computer Science; Algorithmics; Machine Learning; Genetics; SNPs; Rough Sets; Bioinformatics; Bioinformatik;

    Sammanfattning : The use of Machine Learning is rapidly expanding into previously uncharted waters. In the medicine fields there are vast troves of data available from hospitals, biobanks and registries that now are being explored due to the tremendous advancement in computer science and its related hardware. LÄS MER

  5. 14. Elucidation of complex diseases by machine learning

    Författare :Karolina Smolinska Garbulowska; Jan Komorowski; Claes Wadelius; Tuuli Lappalainen; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; machine learning; complex disease; multi-omics; regulatory element; gene regulation; transcription factor motif; networks; rough sets; Bioinformatics; Bioinformatik;

    Sammanfattning : Uncovering the interpretability of models for complex health-related problems is a crucial task that is often neglected in machine learning (ML). The amount of available data makes the problem even more complicated. LÄS MER

  7. 15. Fuzzy and Rough Set Theory in Treatment of Elderly Gastric Cancer Patients

    Författare :Hang Zettervall; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Fuzzy set theory was presented for the first time by Professor Lotfi A. Zadeh from Berkeley University in 1965. In conventional binary logic a statement can be true or false, and there is no place for even a little uncertainty in this judgment. An element either belongs to a set or does not. LÄS MER