Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Antti Honkela"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Background Consider a setting where multiple parties holding sensitive data aim to collaboratively learn population level statistics, but pooling the sensitive data sets is not possible due to privacy concerns and parties are unable to engag
Externí odkaz:
https://doaj.org/article/e8b58c63e214472cb570a208b150005f
Autor:
Tommi Mäklin, Harry A. Thorpe, Anna K. Pöntinen, Rebecca A. Gladstone, Yan Shao, Maiju Pesonen, Alan McNally, Pål J. Johnsen, Ørjan Samuelsen, Trevor D. Lawley, Antti Honkela, Jukka Corander
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
Opportunistic bacterial pathogen species frequently colonise the human gut as a normal part of the ecosystem but strain-level colonisation and competition dynamics in healthy hosts is yet to be established. Authors seek to understand the relationship
Externí odkaz:
https://doaj.org/article/8e93f7b998b34aaf9e526e352acf40b3
Autor:
Bandar AlKnawy, David Bates, Zisis Kozlakidis, George Crooks, Kyu Rhee, Sasu Tarkoma, Antti Honkela, Mollie McKillop
Publikováno v:
BMJ Global Health, Vol 8, Iss 2 (2023)
The COVID-19 pandemic highlighted the need to prioritise mature digital health and data governance at both national and supranational levels to guarantee future health security. The Riyadh Declaration on Digital Health was a call to action to create
Externí odkaz:
https://doaj.org/article/7240276f1c46423b8e25016e81aaf2b2
Autor:
Tommi Mäklin, Teemu Kallonen, Sophia David, Christine J. Boinett, Ben Pascoe, Guillaume Méric, David M. Aanensen, Edward J. Feil, Stephen Baker, Julian Parkhill, Samuel K. Sheppard, Jukka Corander, Antti Honkela
Publikováno v:
Wellcome Open Research, Vol 5 (2021)
Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and esti
Externí odkaz:
https://doaj.org/article/0cb73b1689014c69be5ca5d1203249ad
Publikováno v:
Patterns, Vol 2, Iss 7, Pp 100271- (2021)
Summary: Differential privacy allows quantifying privacy loss resulting from accession of sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as privacy-preserving synthetic data would avoid this limita
Externí odkaz:
https://doaj.org/article/6621fd994528496fb25e007e44770528
Autor:
Hande Topa, Antti Honkela
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-6 (2018)
Abstract Background Genome-wide high-throughput sequencing (HTS) time series experiments are a powerful tool for monitoring various genomic elements over time. They can be used to monitor, for example, gene or transcript expression with RNA sequencin
Externí odkaz:
https://doaj.org/article/a382d5f11c42415f9b79e51a629bd554
Publikováno v:
Biology Direct, Vol 13, Iss 1, Pp 1-12 (2018)
Abstract Background Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if other users are willing to share their private information. Good personalised predictions are vitally
Externí odkaz:
https://doaj.org/article/6369e40b6752481290e96031b8b1f470
Autor:
John A. Lees, Minna Vehkala, Niko Välimäki, Simon R. Harris, Claire Chewapreecha, Nicholas J. Croucher, Pekka Marttinen, Mark R. Davies, Andrew C. Steer, Steven Y. C. Tong, Antti Honkela, Julian Parkhill, Stephen D. Bentley, Jukka Corander
Publikováno v:
Nature Communications, Vol 7, Iss 1, Pp 1-8 (2016)
Plasticity and clonal population structure in bacterial genomes can hinder traditional SNP-based genetic association studies. Here, Corander and colleagues present a method to identify variable-length sequence elements enriched in a phenotype of inte
Externí odkaz:
https://doaj.org/article/cf0152cd3fa84f69ab1a6244a1daed1f
Autor:
Tomasz Dzida, Mudassar Iqbal, Iryna Charapitsa, George Reid, Henk Stunnenberg, Filomena Matarese, Korbinian Grote, Antti Honkela, Magnus Rattray
Publikováno v:
PeerJ, Vol 5, p e3742 (2017)
We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II)
Externí odkaz:
https://doaj.org/article/5dc10e70fa8d487fb5f9f7630200b349
Autor:
Karolis Uziela, Antti Honkela
Publikováno v:
PLoS ONE, Vol 10, Iss 5, p e0126545 (2015)
Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. A
Externí odkaz:
https://doaj.org/article/51ab5bc1341544adbefcbe736f0f55e0