Current Year
1. Berzow D, Descamps D, Obermeier M, Charpentier C, Kaiser R, Guertler L, Eberle J, Wensing A, Sierra S, Ruelle J, Gomes P, Mansinho K, Taylor N, Jensen B, Döring M, Stürmer M, Rockstroh J, Camacho R: Human Immunodeficiency Virus-2 (HIV-2): A Summary of the Present Standard of Care and Treatment Options for Individuals Living with HIV-2 in Western Europe. Clinical Infectious Diseases 2021, 72.
Export
BibTeX
@article{Berzow2021,
TITLE = {Human Immunodeficiency Virus-2 ({HIV-2}): A Summary of the Present Standard of Care and Treatment Options for Individuals Living with {HIV}-2 in {Western Europe}},
AUTHOR = {Berzow, Dirk and Descamps, Diane and Obermeier, Martin and Charpentier, Charlotte and Kaiser, Rolf and Guertler, Lutz and Eberle, Josef and Wensing, Annemarie and Sierra, Saleta and Ruelle, Jean and Gomes, Perpetua and Mansinho, Kamal and Taylor, Ninon and Jensen, Bj{\"o}rn and D{\"o}ring, Matthias and St{\"u}rmer, Martin and Rockstroh, J{\"u}rgen and Camacho, Ricardo},
LANGUAGE = {eng},
ISSN = {1058-4838},
DOI = {10.1093/cid/ciaa275},
PUBLISHER = {The University of Chicago Press},
ADDRESS = {Chicago, IL},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
JOURNAL = {Clinical Infectious Diseases},
VOLUME = {72},
NUMBER = {3},
PAGES = {503--509},
}
Endnote
%0 Journal Article
%A Berzow, Dirk
%A Descamps, Diane
%A Obermeier, Martin
%A Charpentier, Charlotte
%A Kaiser, Rolf
%A Guertler, Lutz
%A Eberle, Josef
%A Wensing, Annemarie
%A Sierra, Saleta
%A Ruelle, Jean
%A Gomes, Perpetua
%A Mansinho, Kamal
%A Taylor, Ninon
%A Jensen, Björn
%A Döring, Matthias
%A Stürmer, Martin
%A Rockstroh, Jürgen
%A Camacho, Ricardo
%+ External Organizations
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Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
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External Organizations
%T Human Immunodeficiency Virus-2 (HIV-2): A Summary of the Present Standard of Care and Treatment Options for Individuals Living with HIV-2 in Western Europe :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-8DEF-D
%R 10.1093/cid/ciaa275
%7 2021
%D 2021
%J Clinical Infectious Diseases
%V 72
%N 3
%& 503
%P 503 - 509
%I The University of Chicago Press
%C Chicago, IL
%@ false
2. Durai DA: Novel graph based algorithms fortranscriptome sequence analysis. Universität des Saarlandes; 2021.
Export
BibTeX
@phdthesis{Duraiphd2020,
TITLE = {Novel graph based algorithms fortranscriptome sequence analysis},
AUTHOR = {Durai, Dilip Ariyur},
LANGUAGE = {eng},
DOI = {10.22028/D291-34158},
SCHOOL = {Universit{\"a}t des Saarlandes},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
}
Endnote
%0 Thesis
%A Durai, Dilip Ariyur
%Y Schulz, Marcel
%A referee: Helms, Volker
%+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
International Max Planck Research School, MPI for Informatics, Max Planck Society
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
%T Novel graph based algorithms fortranscriptome sequence analysis :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-E4D6-5
%R 10.22028/D291-34158
%I Universität des Saarlandes
%C Saarbrücken
%D 2021
%P 143 p.
%V phd
%9 phd
%U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/31478
3. Ebert P, Audano PA, Zhu Q, Rodriguez-Martin B, Porubsky D, Bonder MJ, Sulovari A, Ebler J, Zhou W, Serra Mari R, Yilmaz F, Zhao X, Hsieh P, Lee J, Kumar S, Lin J, Rausch T, Chen Y, Ren J, Santamarina M, Höps W, Ashraf H, Chuang NT, Yang X, Munson KM, Lewis AP, Fairley S, Tallon LJ, Clarke WE, Basile AO, et al.: Haplotype-resolved Diverse Human Genomes and Integrated Analysis of Structural Variation. Science 2021, 372.
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BibTeX
@article{Ebert2021,
TITLE = {Haplotype-resolved Diverse Human Genomes and Integrated Analysis of Structural Variation},
AUTHOR = {Ebert, Peter and Audano, Peter A. and Zhu, Qihui and Rodriguez-Martin, Bernardo and Porubsky, David and Bonder, Marc Jan and Sulovari, Arvis and Ebler, Jana and Zhou, Weichen and Serra Mari, Rebecca and Yilmaz, Feyza and Zhao, Xuefang and Hsieh, PingHsun and Lee, Joyce and Kumar, Sushant and Lin, Jiadong and Rausch, Tobias and Chen, Yu and Ren, Jingwen and Santamarina, Martin and H{\"o}ps, Wolfram and Ashraf, Hufsah and Chuang, Nelson T. and Yang, Xiaofei and Munson, Katherine M. and Lewis, Alexandra P. and Fairley, Susan and Tallon, Luke J. and Clarke, Wayne E. and Basile, Anna O. and Byrska-Bishop, Marta and Corvelo, Andr{\'e} and Evani, Uday S. and Lu, Tsung-Yu and Chaisson, Mark J. P. and Chen, Junjie and Li, Chong and Brand, Harrison and Wenger, Aaron M. and Ghareghani, Maryam and Harvey, William T. and Raeder, Benjamin and Hasenfeld, Patrick and Regier, Allison A. and Abel, Haley J. and Hall, Ira M. and Flicek, Paul and Stegle, Oliver and Gerstein, Mark B. and Tubio, Jose M. C. and Mu, Zepeng and Li, Yang I. and Shi, Xinghua and Hastie, Alex R. and Ye, Kai and Chong, Zechen and Sanders, Ashley D. and Zody, Michael C. and Talkowski, Michael E. and Mills, Ryan E. and Devine, Scott E. and Lee, Charles and Korbel, Jan O. and Marschall, Tobias and Eichler, Evan E.},
LANGUAGE = {eng},
ISSN = {0036-8075},
DOI = {10.1126/science.abf7117},
PUBLISHER = {AAAS},
ADDRESS = {Washington, D.C.},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
JOURNAL = {Science},
VOLUME = {372},
NUMBER = {6537},
EID = {eabf7117},
}
Endnote
%0 Journal Article
%A Ebert, Peter
%A Audano, Peter A.
%A Zhu, Qihui
%A Rodriguez-Martin, Bernardo
%A Porubsky, David
%A Bonder, Marc Jan
%A Sulovari, Arvis
%A Ebler, Jana
%A Zhou, Weichen
%A Serra Mari, Rebecca
%A Yilmaz, Feyza
%A Zhao, Xuefang
%A Hsieh, PingHsun
%A Lee, Joyce
%A Kumar, Sushant
%A Lin, Jiadong
%A Rausch, Tobias
%A Chen, Yu
%A Ren, Jingwen
%A Santamarina, Martin
%A Höps, Wolfram
%A Ashraf, Hufsah
%A Chuang, Nelson T.
%A Yang, Xiaofei
%A Munson, Katherine M.
%A Lewis, Alexandra P.
%A Fairley, Susan
%A Tallon, Luke J.
%A Clarke, Wayne E.
%A Basile, Anna O.
%A Byrska-Bishop, Marta
%A Corvelo, André
%A Evani, Uday S.
%A Lu, Tsung-Yu
%A Chaisson, Mark J. P.
%A Chen, Junjie
%A Li, Chong
%A Brand, Harrison
%A Wenger, Aaron M.
%A Ghareghani, Maryam
%A Harvey, William T.
%A Raeder, Benjamin
%A Hasenfeld, Patrick
%A Regier, Allison A.
%A Abel, Haley J.
%A Hall, Ira M.
%A Flicek, Paul
%A Stegle, Oliver
%A Gerstein, Mark B.
%A Tubio, Jose M. C.
%A Mu, Zepeng
%A Li, Yang I.
%A Shi, Xinghua
%A Hastie, Alex R.
%A Ye, Kai
%A Chong, Zechen
%A Sanders, Ashley D.
%A Zody, Michael C.
%A Talkowski, Michael E.
%A Mills, Ryan E.
%A Devine, Scott E.
%A Lee, Charles
%A Korbel, Jan O.
%A Marschall, Tobias
%A Eichler, Evan E.
%+ External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
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External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
External Organizations
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External Organizations
%T Haplotype-resolved Diverse Human Genomes and Integrated Analysis of Structural Variation :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-BFCA-E
%R 10.1126/science.abf7117
%7 2021
%D 2021
%J Science
%O Science
%V 372
%N 6537
%Z sequence number: eabf7117
%I AAAS
%C Washington, D.C.
%@ false
4. Ebert P, Schulz MH: Fast Detection of Differential Chromatin Domains with SCIDDO. Bioinformatics 2021, 37.
Export
BibTeX
@article{Ebert2021,
TITLE = {Fast detection of differential chromatin domains with {SCIDDO}},
AUTHOR = {Ebert, Peter and Schulz, Marcel Holger},
LANGUAGE = {eng},
ISSN = {1367-4803},
DOI = {10.1093/bioinformatics/btaa960},
PUBLISHER = {Oxford University Press},
ADDRESS = {Oxford},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
JOURNAL = {Bioinformatics},
VOLUME = {37},
NUMBER = {9},
PAGES = {1198--1205},
}
Endnote
%0 Journal Article
%A Ebert, Peter
%A Schulz, Marcel Holger
%+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
%T Fast Detection of Differential Chromatin Domains with SCIDDO :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-D98D-5
%R 10.1093/bioinformatics/btaa960
%2 PMC818969
%7 2021
%D 2021
%J Bioinformatics
%V 37
%N 9
%& 1198
%P 1198 - 1205
%I Oxford University Press
%C Oxford
%@ false
5. Fischer J, Ardakani FB, Kattler K, Walter J, Schulz MH: CpG Content-dependent Associations between Transcription Factors and Histone Modifications. PLoS One 2021, 16.
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BibTeX
@article{fischer:21:cpgtfhm,
TITLE = {{CpG} content-dependent associations between transcription factors and histone modifications},
AUTHOR = {Fischer, Jonas and Ardakani, Fatemeh Behjati and Kattler, Kathrin and Walter, J{\"o}rn and Schulz, Marcel Holger},
LANGUAGE = {eng},
ISSN = {1932-6203},
DOI = {10.1371/journal.pone.0249985},
PUBLISHER = {Public Library of Science},
ADDRESS = {San Francisco, CA},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
JOURNAL = {PLoS One},
VOLUME = {16},
NUMBER = {4},
EID = {0249985},
}
Endnote
%0 Journal Article
%A Fischer, Jonas
%A Ardakani, Fatemeh Behjati
%A Kattler, Kathrin
%A Walter, Jörn
%A Schulz, Marcel Holger
%+ Databases and Information Systems, MPI for Informatics, Max Planck Society
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
%T CpG Content-dependent Associations between Transcription Factors and Histone Modifications :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-5602-5
%R 10.1371/journal.pone.0249985
%7 2021
%D 2021
%J PLoS One
%V 16
%N 4
%Z sequence number: 0249985
%I Public Library of Science
%C San Francisco, CA
%@ false
6. Kitanovski S, Horemheb-Rubio G, Adams O, Gärtner B, Lengauer T, Hoffmann D, Kaiser R: Rhinovirus Prevalence as Indicator for Efficacy of Measures against SARS-CoV-2. BMC Public Health 2021, 21.
Export
BibTeX
@article{Kitaovski2021,
TITLE = {Rhinovirus Prevalence as Indicator for Efficacy of Measures against {SARS}-{CoV}-2},
AUTHOR = {Kitanovski, Simo and Horemheb-Rubio, Gibran and Adams, Ortwin and G{\"a}rtner, Barbara and Lengauer, Thomas and Hoffmann, Daniel and Kaiser, Rolf and {Respiratory Virus Network}},
LANGUAGE = {eng},
ISSN = {1471-2458},
DOI = {10.1186/s12889-021-11178-w},
PUBLISHER = {BioMed Central},
ADDRESS = {London, United Kingdom},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
JOURNAL = {BMC Public Health},
VOLUME = {21},
EID = {1178},
}
Endnote
%0 Journal Article
%A Kitanovski, Simo
%A Horemheb-Rubio, Gibran
%A Adams, Ortwin
%A Gärtner, Barbara
%A Lengauer, Thomas
%A Hoffmann, Daniel
%A Kaiser, Rolf
%A Respiratory Virus Network,
%+ External Organizations
External Organizations
External Organizations
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
%T Rhinovirus Prevalence as Indicator for Efficacy of Measures against SARS-CoV-2 :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-D984-E
%R 10.1186/s12889-021-11178-w
%2 PMC8215636
%7 2021
%D 2021
%J BMC Public Health
%V 21
%Z sequence number: 1178
%I BioMed Central
%C London, United Kingdom
%@ false
7. Marty N, Saeng-Aroon S, Heger E, Thielen A, Obermeier M, Pfeifer N, Kaiser R, Klimkait T: Adapting the Geno2pheno[coreceptor] Tool to HIV-1 Subtype CRF01_AE by Phenotypic Validation Using Clinical Isolates from South-East Asia. Journal of Clinical Virology 2021, 136.
Export
BibTeX
@article{Marty_2021,
TITLE = {Adapting the geno2pheno[coreceptor] tool to {HIV}-1 subtype {CRF01_AE} by phenotypic validation using clinical isolates from {South-East Asia}},
AUTHOR = {Marty, Nina and Saeng-Aroon, Siriphan and Heger, Eva and Thielen, Alexander and Obermeier, Martin and Pfeifer, Nico and Kaiser, Rolf and Klimkait, Thomas},
LANGUAGE = {eng},
ISSN = {1386-6532},
DOI = {10.1016/j.jcv.2021.104755},
PUBLISHER = {Elsevier},
ADDRESS = {Amsterdam},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
JOURNAL = {Journal of Clinical Virology},
VOLUME = {136},
EID = {104755},
}
Endnote
%0 Journal Article
%A Marty, Nina
%A Saeng-Aroon, Siriphan
%A Heger, Eva
%A Thielen, Alexander
%A Obermeier, Martin
%A Pfeifer, Nico
%A Kaiser, Rolf
%A Klimkait, Thomas
%+ External Organizations
External Organizations
External Organizations
External Organizations
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
%T Adapting the Geno2pheno[coreceptor] Tool to HIV-1 Subtype CRF01_AE by Phenotypic Validation Using Clinical Isolates from South-East Asia :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-62DD-1
%R 10.1016/j.jcv.2021.104755
%7 2021
%D 2021
%J Journal of Clinical Virology
%V 136
%Z sequence number: 104755
%I Elsevier
%C Amsterdam
%@ false
8. Metzler S: Structural Building Blocks in Graph Data. Universität des Saarlandes; 2021.
Abstract
Graph data nowadays easily become so large that it is infeasible to study the underlying structures manually. Thus, computational methods are needed to uncover large-scale structural information. In this thesis, we present methods to understand and summarise large networks.
We propose the hyperbolic community model to describe groups of more densely connected nodes within networks using very intuitive parameters. The model accounts for a
frequent connectivity pattern in real data: a few community members are highly interconnected; most members mainly have ties to this core. Our model fits real data much better than previously-proposed models. Our corresponding random graph generator, HyGen, creates graphs with realistic intra-community structure.
Using the hyperbolic model, we conduct a large-scale study of the temporal evolution of communities on online question–answer sites. We observe that the user activity within a community is constant with respect to its size throughout its lifetime, and a small group of users is responsible for the majority of the social interactions.
We propose an approach for Boolean tensor clustering. This special tensor factorisation is restricted to binary data and assumes that one of the tensor directions has only non-overlapping factors. These assumptions – valid for many real-world data, in particular time-evolving networks – enable the use of bitwise operators and lift much of the computational complexity from the task.
Export
BibTeX
@phdthesis{SaskiaDiss21,
TITLE = {Structural Building Blocks in Graph Data},
AUTHOR = {Metzler, Saskia},
LANGUAGE = {eng},
SCHOOL = {Universit{\"a}t des Saarlandes},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
ABSTRACT = {Graph data nowadays easily become so large that it is infeasible to study the underlying structures manually. Thus, computational methods are needed to uncover large-scale structural information. In this thesis, we present methods to understand and summarise large networks. We propose the hyperbolic community model to describe groups of more densely connected nodes within networks using very intuitive parameters. The model accounts for a frequent connectivity pattern in real data: a few community members are highly interconnected; most members mainly have ties to this core. Our model fits real data much better than previously-proposed models. Our corresponding random graph generator, HyGen, creates graphs with realistic intra-community structure. Using the hyperbolic model, we conduct a large-scale study of the temporal evolution of communities on online question--answer sites. We observe that the user activity within a community is constant with respect to its size throughout its lifetime, and a small group of users is responsible for the majority of the social interactions. We propose an approach for Boolean tensor clustering. This special tensor factorisation is restricted to binary data and assumes that one of the tensor directions has only non-overlapping factors. These assumptions -- valid for many real-world data, in particular time-evolving networks -- enable the use of bitwise operators and lift much of the computational complexity from the task.},
}
Endnote
%0 Thesis
%A Metzler, Saskia
%Y Miettinen, Pauli
%Y Weikum, Gerhard
%Y Günnemann, Stephan
%+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
International Max Planck Research School, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
External Organizations
%T Structural Building Blocks in Graph Data : Characterised by Hyperbolic Communities and Uncovered by Boolean Tensor Clustering
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-0BC1-2
%I Universität des Saarlandes
%C Saarbrücken
%D 2021
%P 196 p.
%V phd
%9 phd
%X Graph data nowadays easily become so large that it is infeasible to study the underlying structures manually. Thus, computational methods are needed to uncover large-scale structural information. In this thesis, we present methods to understand and summarise large networks.
We propose the hyperbolic community model to describe groups of more densely connected nodes within networks using very intuitive parameters. The model accounts for a
frequent connectivity pattern in real data: a few community members are highly interconnected; most members mainly have ties to this core. Our model fits real data much better than previously-proposed models. Our corresponding random graph generator, HyGen, creates graphs with realistic intra-community structure.
Using the hyperbolic model, we conduct a large-scale study of the temporal evolution of communities on online question–answer sites. We observe that the user activity within a community is constant with respect to its size throughout its lifetime, and a small group of users is responsible for the majority of the social interactions.
We propose an approach for Boolean tensor clustering. This special tensor factorisation is restricted to binary data and assumes that one of the tensor directions has only non-overlapping factors. These assumptions – valid for many real-world data, in particular time-evolving networks – enable the use of bitwise operators and lift much of the computational complexity from the task.
9. Scherer M, Schmidt F, Lazareva O, Walter J, Baumbach J, Schulz MH, List M: Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation. Nature Computational Science 2021, 1.
Export
BibTeX
@article{Scherer2021,
TITLE = {Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation},
AUTHOR = {Scherer, Michael and Schmidt, Florian and Lazareva, Olga and Walter, J{\"o}rn and Baumbach, Jan and Schulz, Marcel Holger and List, Markus},
LANGUAGE = {eng},
ISSN = {2662-8457},
DOI = {10.1038/s43588-021-00038-7},
PUBLISHER = {Nature Research},
ADDRESS = {London},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
JOURNAL = {Nature Computational Science},
VOLUME = {1},
}
Endnote
%0 Journal Article
%A Scherer, Michael
%A Schmidt, Florian
%A Lazareva, Olga
%A Walter, Jörn
%A Baumbach, Jan
%A Schulz, Marcel Holger
%A List, Markus
%+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
%T Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-2A4A-7
%R 10.1038/s43588-021-00038-7
%7 2021
%D 2021
%J Nature Computational Science
%V 1
%I Nature Research
%C London
%@ false
10. Scherer M: Computational solutions for addressing heterogeneity in DNA methylation data. Universität des Saarlandes; 2021.
Export
BibTeX
@phdthesis{Schererphd2020,
TITLE = {Computational solutions for addressing heterogeneity in {DNA} methylation data},
AUTHOR = {Scherer, Michael},
LANGUAGE = {eng},
DOI = {10.22028/D291-33808},
SCHOOL = {Universit{\"a}t des Saarlandes},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
DATE = {2021},
}
Endnote
%0 Thesis
%A Scherer, Michael
%Y Lengauer, Thomas
%A referee: Walther, Jörn
%A referee: Marschall, Tobias
%+ Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
International Max Planck Research School, MPI for Informatics, Max Planck Society
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
External Organizations
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society
%T Computational solutions for addressing heterogeneity in DNA methylation data :
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-BA18-C
%R 10.22028/D291-33808
%I Universität des Saarlandes
%C Saarbrücken
%D 2021
%P 147 p.
%V phd
%9 phd
%U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/31186