Alexander Schliep
Alexander Schliep
Associate Professor, Gothenburg University
Verified email at - Homepage
Cited by
Cited by
Clustering cancer gene expression data: a comparative study
MC De Souto, IG Costa, DS De Araujo, TB Ludermir, A Schliep
BMC bioinformatics 9 (1), 1-14, 2008
Using hidden Markov models to analyze gene expression time course data
A Schliep, A Schönhuth, C Steinhoff
Bioinformatics 19 (suppl_1), i255-i263, 2003
Selecting signature oligonucleotides to identify organisms using DNA arrays
L Kaderali, A Schliep
Bioinformatics 18 (10), 1340-1349, 2002
ProClust: improved clustering of protein sequences with an extended graph-based approach
P Pipenbacher, A Schliep, S Schneckener, A Schönhuth, D Schomburg, ...
Bioinformatics 18 (suppl_2), S182-S191, 2002
Clustering protein sequences—structure prediction by transitive homology
E Bolten, A Schliep, S Schneckener, D Schomburg, R Schrader
Bioinformatics 17 (10), 935-941, 2001
CLEVER: clique-enumerating variant finder
T Marschall, IG Costa, S Canzar, M Bauer, GW Klau, A Schliep, ...
Bioinformatics 28 (22), 2875-2882, 2012
Ranking and selecting clustering algorithms using a meta-learning approach
MCP De Souto, RBC Prudencio, RGF Soares, DSA De Araujo, IG Costa, ...
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
Analyzing gene expression time-courses
A Schliep, IG Costa, C Steinhoff, A Schonhuth
IEEE/ACM Transactions on computational biology and bioinformatics 2 (3), 179-193, 2005
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
Turtle: Identifying frequent k -mers with cache-efficient algorithms
RS Roy, D Bhattacharya, A Schliep
Bioinformatics 30 (14), 1950-1957, 2014
Group testing with DNA chips: generating designs and decoding experiments
A Schliep, DC Torney, S Rahmann
Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE …, 2003
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
Comparative study on normalization procedures for cluster analysis of gene expression datasets
MCP De Souto, DSA De Araujo, IG Costa, RGF Soares, TB Ludermir, ...
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
Optimal robust non-unique probe selection using integer linear programming
GW Klau, S Rahmann, A Schliep, M Vingron, K Reinert
Bioinformatics 20 (suppl_1), i186-i193, 2004
Single cell genome analysis of an uncultured heterotrophic stramenopile
RS Roy, DC Price, A Schliep, G Cai, A Korobeynikov, HS Yoon, EC Yang, ...
Scientific reports 4 (1), 1-8, 2014
Constrained mixture estimation for analysis and robust classification of clinical time series
IG Costa, A Schönhuth, C Hafemeister, A Schliep
Bioinformatics 25 (12), i6-i14, 2009
The discriminant power of RNA features for pre-miRNA recognition
I de ON Lopes, A Schliep, ACP de LF de Carvalho
BMC bioinformatics 15 (1), 1-11, 2014
Robust inference of groups in gene expression time-courses using mixtures of HMMs
A Schliep, C Steinhoff, A Schönhuth
Bioinformatics 20 (suppl_1), i283-i289, 2004
Context-specific independence mixture modeling for positional weight matrices
B Georgi, A Schliep
Bioinformatics 22 (14), e166-e173, 2006
Automatic blood glucose prediction with confidence using recurrent neural networks
J Martinsson, A Schliep, B Eliasson, C Meijner, S Persson, O Mogren
Khd@ ijcai, 2018
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