Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kalifa Manjang"'
Autor:
Kalifa Manjang, Shailesh Tripathi, Olli Yli-Harja, Matthias Dehmer, Galina Glazko, Frank Emmert-Streib
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-18 (2021)
Abstract The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogati
Externí odkaz:
https://doaj.org/article/05e4f37fd1ac4cefba70c6651c466311
Publikováno v:
Frontiers in Genetics, Vol 12 (2021)
High-throughput technologies do not only provide novel means for basic biological research but also for clinical applications in hospitals. For instance, the usage of gene expression profiles as prognostic biomarkers for predicting cancer progression
Externí odkaz:
https://doaj.org/article/70b5d43c39bd4e81b304b17aa047c8fd
Autor:
Kalifa Manjang, Frank Emmert Streib, Samar Bashath, Matthias Dehmer, Shailesh Tripathi, Nadeesha Perera
Publikováno v:
Information Sciences. 585:498-528
In recent years, many applications are using various forms of deep learning models. Such methods are usually based on traditional learning paradigms requiring the consistency of properties among the feature spaces of the training and test data and al
Autor:
Kalifa, Manjang, Shailesh, Tripathi, Olli, Yli-Harja, Matthias, Dehmer, Galina, Glazko, Frank, Emmert-Streib
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-18 (2021)
Scientific Reports
Scientific Reports
The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::07d4f548117e0e70b9d46a94a37a9a32
https://trepo.tuni.fi/handle/10024/130661
https://trepo.tuni.fi/handle/10024/130661
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is chall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::73483799bfcd2c9cdaf955156be89fd2
https://trepo.tuni.fi/handle/10024/127779
https://trepo.tuni.fi/handle/10024/127779