Zmiana języka

Projects search

Statistical and machine learning challenges in classification and integration of molecular and genomic data

2016/23/D/ST6/03613

Keywords

Descriptors

  • ST6_11: Uczenie maszynowe, statystyczne przetwarzanie danych i zastosowanie w przetwarzaniu sygnałów
  • NZ2_8: Biologia obliczeniowa
  • NZ2_9: Biologia systemowa

Panel

ST6 – Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution

Uniwersytet Warszawski, Wydział Matematyki, Informatyki i Mechaniki

Voivodeship: mazowieckie

Other projects carried out by the institution »

Principal investigator (from the host institution)

dr Neo Christopher Honghoon Chung

Number of co-investigators in the project: 2

Call

SONATA 12 – announced on 2016-09-15

Amount awarded
424 029 PLN
Project start date
2017-08-03
Project end date
2021-02-02
Project duration
42 months (the same as in the proposal)
Project status
Project settled

Project description

Download the project description in a pdf file

Note — project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. 27" Monitor (Dell UltraSharp U2717D). Cost: 2 450 PLN
  2. Macbook Pro 15' 2.7 GHz. Cost: 13 899 PLN
  3. Network-attached storage (NAS).

Information in the final report

Publication in academic press/journals (6)

  1. Jaccard/Tanimoto similarity test and estimation methods for biological presence-absence data

    Authors:
    Neo Christopher Chung, Błażej Miasojedow, Michał Startek, Anna Gambin
    Academic press:
    BMC Bioinformatics (year: 2019, volume: 20, pages: 644), Publisher: Springer Nature
    Status:
    Published

  2. Truncated robust principal component analysis and noise reduction for single cell RNA-seq data

    Authors:
    Krzysztof Gogolewski, Maciej Sykulski, Neo Christopher Chung, Anna Gambin
    Academic press:
    Journal of Computational Biology (year: 2019, volume: 26, pages: 782-793), Publisher: Mary Ann Liebert
    Status:
    Published
    DOI:
    10.1089/cmb.2018.0255 – link to the publication

  3. Unsupervised Classification of Multi-Omics Data during Cardiac Remodeling using Deep Learning

    Authors:
    Neo Christopher Chung, Bilal Mirza, Howard Choi, Jie Wang, Ding Wang, Peipei Ping, Wei Wang
    Academic press:
    Methods (year: 2019, volume: 166, pages: 66-73), Publisher: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.ymeth.2019.03.004 – link to the publication

  4. Statistical significance of cluster membership for unsupervised evaluation of cell identities

    Authors:
    Neo Christopher Chung
    Academic press:
    Bioinformatics (year: 2020, volume: 36, pages: 3107-3114), Publisher: Oxford University Press
    Status:
    Published
    DOI:
    10.1093/bioinformatics/btaa087 – link to the publication

  5. Identifying temporal molecular signatures underlying cardiovascular diseases: A data science platform

    Authors:
    Neo Christopher Chung, Howard Choi, Ding Wang, Bilal Mirza, Alexander R Pelletier, Dibakar Sigdel, Wei Wang, Peipei Ping
    Academic press:
    Journal of Molecular and Cellular Cardiology (year: 2020, volume: 145, pages: 54-58), Publisher: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.yjmcc.2020.05.020 – link to the publication

  6. Deep learning in oncological radiomics and challenges of interpretability and data harmonization

    Authors:
    Panagiotis Papadimitroulas, Lennart Brocki, Neo Christopher Chung, Wistan Marchadour, Franck Vermet, Laurent Gaubert, Vasilis Eleftheriadis, Dimitris Plachouris, Dimitris Visvikis, George Kagadis, Mathieu Hatt
    Status:
    Accepted for publication

Articles in post-conference publications (3)

  1. Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA-seq Data

    Authors:
    Krzysztof Gogolewski, Maciej Sykulski, Neo Christopher Chung, Anna Gambin
    Conference:
    International Symposium on Bioinformatics Research and Applications (year: 2018, pages: 335-346), Publisher: Springer
    Date:
    conference 08/06 - 11/06
    Status:
    Published

  2. Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models

    Authors:
    Lennart Brocki, Neo Christopher Chung
    Conference:
    18th IEEE International Conference On Machine Learning And Applications (ICMLA) (year: 2019, pages: 1771-1778), Publisher: IEEE Xplore
    Date:
    conference 43815
    Status:
    Published

  3. Input Bias in Rectified Gradients and Modified Saliency Maps

    Authors:
    Lennart Brocki, Neo Christopher Chung
    Conference:
    2021 IEEE International Conference on Big Data and Smart Computing (year: 2021), Publisher: IEEE Xplore
    Status:
    Accepted for publication

« New search

Graphic design and implementation: Jakub Piotrowski