Author

Bodo M. H. Lange

Alacris (Germany)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Systems Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Christoph WierlingiD· 2 shared Daniel WeindliD· 2 shared Jan HasenaueriD· 2 shared Leonard SchmiesteriD· 2 shared Alexey A. ShadriniD· 1 shared Artur MuradyaniD· 1 shared Dilan PathiranaiD· 1 shared Fabian FröhlichiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

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10 top collaborators · 40 mutual co-author links

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2 shared papersSystems Biology

Christoph WierlingORCID

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2 papers

Recent·Most cited

Mini-batch optimization enables training of ODE models on large-scale datasets

Paul L. Stapor, Leonard Schmiester, Christoph Wierling, Simon Merkt, Dilan Pathirana, Bodo M. H. Lange, Daniel Weindl, Jan Hasenauer

This paper applies mini-batch optimization to ODE models, improving efficiency and results on a cancer signaling dataset.

Nature Communications · Jan 10, 2022Peer-reviewedSystems Biology

Efficient parameterization of large-scale mechanistic models enables drug response prediction for cancer cell lines

Fabian Fröhlich, Thomas Kessler, Daniel Weindl, Alexey A. Shadrin, Leonard Schmiester, Hendrik Hache, Artur Muradyan, Moritz Schütte, Ji‐Hyun Lim, Matthias Heinig, Fabian Joachim Theis, Hans Rudolf Lehrach, Christoph Wierling, Bodo M. H. Lange, Jan Hasenauer

The paper presents a computational framework to parameterize large-scale mechanistic models for predicting drug response in cancer cell lines using exome and transcriptome data, achieving higher accuracy than statistical approaches.

Cell Systems · Nov 28, 2018Peer-reviewedSystems Biology