Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Lonneke Scheffer"'
Autor:
Rahmad Akbar, Philippe A. Robert, Cédric R. Weber, Michael Widrich, Robert Frank, Milena Pavlović, Lonneke Scheffer, Maria Chernigovskaya, Igor Snapkov, Andrei Slabodkin, Brij Bhushan Mehta, Enkelejda Miho, Fridtjof Lund-Johansen, Jan Terje Andersen, Sepp Hochreiter, Ingrid Hobæk Haff, Günter Klambauer, Geir Kjetil Sandve, Victor Greiff
Publikováno v:
mAbs, Vol 14, Iss 1 (2022)
Generative machine learning (ML) has been postulated to become a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing
Externí odkaz:
https://doaj.org/article/dcc3e950ba4a40b789231de4ffed3cb1
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 3, p e1008549 (2021)
Externí odkaz:
https://doaj.org/article/ac7e4f9810b345429fa5c3b39f954fea
Autor:
Philippe A. Robert, Rahmad Akbar, Robert Frank, Milena Pavlović, Michael Widrich, Igor Snapkov, Andrei Slabodkin, Maria Chernigovskaya, Lonneke Scheffer, Eva Smorodina, Puneet Rawat, Brij Bhushan Mehta, Mai Ha Vu, Ingvild Frøberg Mathisen, Aurél Prósz, Krzysztof Abram, Alex Olar, Enkelejda Miho, Dag Trygve Tryslew Haug, Fridtjof Lund-Johansen, Sepp Hochreiter, Ingrid Hobæk Haff, Günter Klambauer, Geir Kjetil Sandve, Victor Greiff
Publikováno v:
Nature Computational Science. 2:845-865
Publikováno v:
Bioinformatics. 38:4230-4232
Motivation Adaptive immune receptor (AIR) repertoires (AIRRs) record past immune encounters with exquisite specificity. Therefore, identifying identical or similar AIR sequences across individuals is a key step in AIRR analysis for revealing converge
Autor:
Shiva Dahal-Koirala, Gabriel Balaban, Ralf Stefan Neumann, Lonneke Scheffer, Knut Erik Aslaksen Lundin, Victor Greiff, Ludvig Magne Sollid, Shuo-Wang Qiao, Geir Kjetil Sandve
Publikováno v:
Briefings in Bioinformatics. 23
T-cell receptor (TCR) sequencing has enabled the development of innovative diagnostic tests for cancers, autoimmune diseases and other applications. However, the rarity of many T-cell clonotypes presents a detection challenge, which may lead to misdi
Autor:
Milena Pavlović, Keshav Motwani, Lonneke Scheffer, Maria Chernigovskaya, Chakravarthi Kanduri, Victor Greiff, Geir Kjetil Sandve
BackgroundMachine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86e68a10f7a1f4b971b78bf3d04bdfa7
http://hdl.handle.net/10852/94308
http://hdl.handle.net/10852/94308
Autor:
Ingrid Hobæk Haff, Ludvig M. Sollid, Ivana Mikocziova, José F. Gutierrez-Marcos, Maria Chernigovskaya, Brij Bhushan Mehta, Philippe Robert, Milena Pavlović, Igor Snapkov, Rahmad Akbar, Lonneke Scheffer, Andrei Slabodkin, Cédric R. Weber, Habib Bashour, Geir Kjetil Sandve, Victor Greiff
Publikováno v:
Genome Research, 31 (12)
Genome Res
Genome Res
The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire and, consequently, (auto)antigen recognition. VDJ recombination follows probabilistic r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55b4d8cccc01c0465a03a7a6b21d0aff
https://hdl.handle.net/20.500.11850/529014
https://hdl.handle.net/20.500.11850/529014
SummaryAdaptive immune receptor (AIR) repertoires (AIRRs) record past immune encounters with exquisite specificity. Therefore, identifying identical or similar AIR sequences across individuals is a key step in AIRR analysis for revealing convergent i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4094d5cc223c8a85729130aad6c6a78
https://doi.org/10.1101/2021.10.30.466600
https://doi.org/10.1101/2021.10.30.466600
Autor:
Chakravarthi Kanduri, Alexandre Almeida Costa, Eivind Hovig, Antonio Martini, Michael Widrich, Ghadi S. Al Hajj, Ingrid Hobæk Haff, Ivar Grytten, Radmila Kompova, Andrei Slabodkin, Cédric R. Weber, Ludvig M. Sollid, Gabriel Balaban, Knut Dagestad Rand, Fabian L. M. Bernal, Victor Greiff, Gur Yaari, Marieke L. Kuijjer, Artur Rocha, Enrico Riccardi, Knut Waagan, Brian Corrie, Igor Snapkov, Lonneke Scheffer, Nikolay Vazov, Milena Pavlović, Robert Frank, Dmytro Titov, Maria Chernigovskaya, Johan Pensar, Rahmad Akbar, Todd M. Brusko, Scott Christley, Keshav Motwani, Geir Kjetil Sandve, Philippe Robert, Thomas Minotto, Ping-Han Hsieh, Sveinung Gundersen, Christin Lund-Andersen, Lindsay G. Cowell, Günter Klambauer
Publikováno v:
Nat Mach Intell
Adaptive immune receptor repertoires (AIRR) are key targets for biomedical research as they record past and ongoing adaptive immune responses. The capacity of machine learning (ML) to identify complex discriminative sequence patterns renders it an id
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65225dec4d5ad9e94648449a645b13a2
https://europepmc.org/articles/PMC10312379/
https://europepmc.org/articles/PMC10312379/
Autor:
Milena Pavlović, Michael Widrich, Günter Klambauer, Fridtjof Lund-Johansen, Greiff, Sepp Hochreiter, Lonneke Scheffer, Maria Chernigovskaya, Cédric R. Weber, Philippe Robert, Geir Kjetil Sandve, Brij Bhushan Mehta, Ingrid Hobæk Haff, Rahmad Akbar, Igor Snapkov, Andersen Jt, Andrei Slabodkin, Enkelejda Miho, Frank R
Generative machine learning (ML) has been postulated to be a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing arbi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2df2edb1a2fc2495e4ffd6ab29e4bab
https://doi.org/10.1101/2021.07.08.451480
https://doi.org/10.1101/2021.07.08.451480