Mariia Chernigovskaia

Articles

Article: NUCLEIC ACIDS RESEARCH. 2025;53(3):gkaf025
Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning
Chernigovskaya M; Pavlovic M; Kanduri C; Gielis S; Robert PA; Scheffer L; Slabodkin A; Haff IH; Meysman P; Yaari G; Sandve GK; Greiff V
Article: BRIEFINGS IN BIOINFORMATICS. 2024;25(6):bbae537
Predictability of antigen binding based on short motifs in the antibody CDRH3
Scheffer L; Reber EE; Mehta BB; Pavlovic M; Chernigovskaya M; Richardson E; Akbar R; Lund-Johansen F; Greiff V; Haff IH; Sandve GK
Journal article: COMMUNICATIONS BIOLOGY. 2024;7(1):922
Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability.
Bashour H; Smorodina E; Pariset M; Zhong J; Akbar R; Chernigovskaya M; Lê Quý K; Snapkow I; Rawat P; Krawczyk K; Sandve GK; Gutierrez-Marcos J; Gutierrez DN-Z; Andersen JT; Greiff V
Article: NPJ SYSTEMS BIOLOGY AND APPLICATIONS. 2024;10(1):73
Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling.
Lê Quý K; Chernigovskaya M; Stensland M; Singh S; Leem J; Revale S; Yadin DA; Nice FL; Povall C; Minns DH; Galson JD; Nyman TA; Snapkow I; Greiff V
Article: SCIENTIFIC REPORTS. 2023;13(1):17714
Human thymic putative CD8αα precursors exhibit a biased TCR repertoire in single cell AIRR-seq.
Heimli M; Tennebø Flåm S; Sagsveen Hjorthaug H; Bjørnstad PM; Chernigovskaya M; Le QK; Tekpli X; Greiff V; Lie BA
Article: FRONTIERS IN CARDIOVASCULAR MEDICINE. 2023;10:1221620
Application and challenges of TCR and BCR sequencing to investigate T- and B-cell clonality in elastase-induced experimental murine abdominal aortic aneurysm.
Elster C; Ommer-Bläsius M; Lang A; Vajen T; Pfeiler S; Feige M; Yau Pang T; Böttenberg M; Verheyen S; Lê Quý K; Chernigovskaya M; Kelm M; Winkels H; Schmidt SV; Greiff V; Gerdes N
Article: MABS. 2022;14(1):2031482
In silico proof of principle of machine learning-based antibody design at unconstrained scale
Akbar R; Robert PA; Weber CR; Widrich M; Frank R; Pavlovic M; Scheffer L; Chernigovskaya M; Snapkov I; Slabodkin A; Mehta BB; Miho E; Lund-Johansen F; Andersen JT; Hochreiter S; Haff IH; Klambauer G; Sandve GK; Greiff V
Article: GIGASCIENCE. 2022;12:giad074
simAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods
Kanduri C; Scheffer L; Pavlovic M; Rand KD; Chernigovskaya M; Pirvandy O; Yaari G; Greiff V; Sandve GK
Article: NATURE COMPUTATIONAL SCIENCE. 2022;2(12):845-865
Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction.
Robert PA; Akbar R; Frank R; Pavlović M; Widrich M; Snapkov I; Slabodkin A; Chernigovskaya M; Scheffer L; Smorodina E; Rawat P; Mehta BB; Vu MH; Mathisen IF; Prósz A; Abram K; Olar A; Miho E; Haug DTT; Lund-Johansen F; Hochreiter S; Haff IH; Klambauer G; Sandve GK; Greiff V
Journal article: IMMUNOINFORMATICS. 2022;6:100012
A Nextflow pipeline for T-cell receptor repertoire reconstruction and analysis from RNA sequencing data
Rubio T; Chernigovskaya M; Marquez S; Marti C; Izquierdo-Altarejos P; Urios A; Montoliu C; Felipo V; Conesa A; Greiff V; Tarazona S
Article: GIGASCIENCE. 2022;11:giac046
Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification
Kanduri C; Pavlovic M; Scheffer L; Motwani K; Chernigovskaya M; Greiff V; Sandve GK
Article: GENOME RESEARCH. 2021;31(12):2209-2224
Individualized VDJ recombination predisposes the available Ig sequence space
Slabodkin A; Chernigovskaya M; Mikocziova I; Akbar R; Scheffer L; Pavlovic M; Bashour H; Snapkov I; Mehta BB; Weber CR; Gutierrez-Marcos J; Sollid LM; Haff IH; Sandve GK; Robert PA; Greiff V
Article: NATURE MACHINE INTELLIGENCE. 2021;3(11):936-944
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires
Pavlovic M; Scheffer L; Motwani K; Kanduri C; Kompova R; Vazov N; Waagan K; Bernal FLM; Costa AA; Corrie B; Akbar R; Al Hajj GS; Balaban G; Brusko TM; Chernigovskaya M; Christley S; Cowell LG; Frank R; Grytten I; Gundersen S; Haff IH; Hovig E; Hsieh P-H; Klambauer G; Kuijjer ML; Lund-Andersen C; Martini A; Minotto T; Pensar J; Rand K; Riccardi E; Robert PA; Rocha A; Slabodkin A; Snapkov I; Sollid LM; Titov D; Weber CR; Widrich M; Yaari G; Greiff V; Sandve GKAll authors
Article: EBIOMEDICINE. 2021;68:103429
TCR repertoire diversity in Multiple Sclerosis: High-dimensional bioinformatics analysis of sequences from brain, cerebrospinal fluid and peripheral blood
Amoriello R; Chernigovskaya M; Greiff V; Carnasciali A; Massacesi L; Barilaro A; Repice AM; Biagioli T; Aldinucci A; Muraro PA; Laplaud DA; Lossius A; Ballerini C

All other publications

Preprint: BIORXIV. 2024
Systematic benchmarking of mass spectrometry-based antibody sequencing reveals methodological biases
Chernigovskaya M; Quý KL; Stensland M; Singh S; Nelson R; Yilmaz M; Kalogeropoulos K; Sinitcyn P; Patel A; Castellana N; Bonissone S; Foss S; Andersen JT; Sandve GK; Jenkins TP; Noble WS; Nyman TA; Snapkow I; Greiff V
Preprint: BIORXIV. 2024
Training data composition determines machine learning generalization and biological rule discovery
Ursu E; Minnegalieva A; Rawat P; Chernigovskaya M; Tacutu R; Sandve GK; Robert P; Greiff V
Preprint: BIORXIV. 2023
Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning
Chernigovskaya M; Pavlović M; Kanduri C; Gielis S; Robert P; Scheffer L; Slabodkin A; Haff IH; Meysman P; Yaari G; Sandve GK; Greiff V
Review: TRENDS IN BIOTECHNOLOGY. 2022;40(4):463-481
Progress and challenges in mass spectrometry-based analysis of antibody repertoires
Snapkov I; Chernigovskaya M; Sinitcyn P; Khang LQ; Nyman TA; Greiff V

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