Articles with public access mandates - Alexander SchliepLearn more
Not available anywhere: 3
AI-assisted synthesis prediction
S Johansson, A Thakkar, T Kogej, E Bjerrum, S Genheden, T Bastys, ...
Drug Discovery Today: Technologies 32, 65-72, 2019
Mandates: Knut and Alice Wallenberg Foundation
Using HaMMLET for Bayesian Segmentation of WGS Read-Depth Data
J Wiedenhoeft, A Schliep
Copy Number Variants: Methods and Protocols, 83-93, 2018
Mandates: US National Institutes of Health
Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes
S Johansson, O Engkvist, MH Chehreghani, A Schliep
2023 IEEE International Conference on Big Data (BigData), 5260-5265, 2023
Mandates: Knut and Alice Wallenberg Foundation
Available somewhere: 13
The Global Museum: natural history collections and the future of evolutionary science and public education
FT Bakker, A Antonelli, JA Clarke, JA Cook, SV Edwards, PGP Ericson, ...
PeerJ 8, e8225, 2020
Mandates: Knut and Alice Wallenberg Foundation, Swedish Research Council, European …
Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics
GA Bravo, A Antonelli, CD Bacon, K Bartoszek, MPK Blom, S Huynh, ...
PeerJ 7, e6399, 2019
Mandates: US National Science Foundation, US Agency for International Development …
Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment
N Judd, B Sauce, J Wiedenhoeft, J Tromp, B Chaarani, A Schliep, ...
Proceedings of the National Academy of Sciences 117 (22), 12411-12418, 2020
Mandates: US National Institutes of Health, German Research Foundation, National …
Bayesian optimization in ab initio nuclear physics
A Ekström, C Forssén, C Dimitrakakis, D Dubhashi, HT Johansson, ...
Journal of Physics G: Nuclear and Particle Physics 46 (9), 095101, 2019
Mandates: Swedish Research Council, European Commission
Using active learning to develop machine learning models for reaction yield prediction
S Viet Johansson, H Gummesson Svensson, E Bjerrum, A Schliep, ...
Molecular Informatics 41 (12), 2200043, 2022
Mandates: Knut and Alice Wallenberg Foundation
Predicting progression and cognitive decline in amyloid-positive patients with Alzheimer’s disease
HV Dansson, L Stempfle, H Egilsdóttir, A Schliep, E Portelius, K Blennow, ...
Alzheimer's Research & Therapy 13, 1-16, 2021
Mandates: US Department of Defense, US National Institutes of Health, Canadian …
Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models
M Seifert, M Strickert, A Schliep, I Grosse
Bioinformatics 27 (12), 1645-1652, 2011
Mandates: German Research Foundation
Deep learning for deep waters: an expert-in-the-loop machine learning framework for marine sciences
I Ryazanov, AT Nylund, D Basu, IM Hassellöv, A Schliep
Journal of Marine Science and Engineering 9 (2), 169, 2021
Mandates: Knut and Alice Wallenberg Foundation
Embracing heterogeneity: building the tree of life and the future of phylogenomics
GA Bravo, A Antonelli, CD Bacon, K Bartoszek, M Blom, S Huynh, ...
PeerJ Preprints 6, e26449v3, 2018
Mandates: US National Science Foundation, Knut and Alice Wallenberg Foundation …
Fast bayesian inference of copy number variants using hidden Markov models with wavelet compression
J Wiedenhoeft, E Brugel, A Schliep
PLOS Computational Biology 12 (5), e1004871, 2016
Mandates: US National Science Foundation, US National Institutes of Health
Fast parallel construction of variable-length Markov chains
J Gustafsson, P Norberg, JR Qvick-Wester, A Schliep
BMC bioinformatics 22, 1-23, 2021
Mandates: Swedish Research Council for Environment, Agricultural Sciences and Spatial …
De novo generated combinatorial library design
SV Johansson, MH Chehreghani, O Engkvist, A Schliep
Digital Discovery 3 (1), 122-135, 2024
Mandates: Knut and Alice Wallenberg Foundation
Bayesian localization of CNV candidates in WGS data within minutes
J Wiedenhoeft, A Cagan, R Kozhemyakina, R Gulevich, A Schliep
Algorithms for Molecular Biology 14, 1-16, 2019
Mandates: US National Institutes of Health
Publication and funding information is determined automatically by a computer program