Malmström, Lars

Macromolecular modeling and design in Rosetta: recent methods and frameworks

Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 888

An automated pipeline for high-throughput label-free quantitative proteomics

Weisser, H., Nahnsen, S., Grossmann, J., Nilse, L., Quandt, A., Brauer, H., Sturm, M., Kenar, E., Kohlbacher, O., Aebersold, R., et al. (2013) · Journal of Proteome Research

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 160

Quantitative proteomic characterization of the lung extracellular matrix in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

Åhrman, E., Hallgren, O., Malmström, L., Hedström, U., Malmström, A., Bjermer, L., Zhou, X.-H., Westergren-Thorsson, G., & Malmström, J. (2018) · Journal of Proteomics

Advanced Proteomics Techniques and ApplicationsInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

Cited by 88

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Gueto-Tettay, C., Tang, D., Happonen, L., Heusel, M., Khakzad, H., Malmström, J., & Malmström, L. (2023) · PLOS Computational Biology

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 12

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Gueto-Tettay, C., Tang, D., Happonen, L., Heusel, M., Khakzad, H., Malmström, J., & Malmström, L. (2022) · PLoS Computational Biology

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 12