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  • 1. Altenhoff, Adrian M.
    et al.
    Boeckmann, Brigitte
    Capella-Gutierrez, Salvador
    Dalquen, Daniel A.
    DeLuca, Todd
    Forslund, Kristoffer
    Huerta-Cepas, Jaime
    Linard, Benjamin
    Pereira, Cecile
    Pryszcz, Leszek P.
    Schreiber, Fabian
    da Silva, Alan Sousa
    Szklarczyk, Damian
    Train, Clement-Marie
    Bork, Peer
    Lecompte, Odile
    von Mering, Christian
    Xenarios, Ioannis
    Sjölander, Kimmen
    Juhl Jensen, Lars
    Martin, Maria J.
    Muffato, Matthieu
    Gabaldon, Toni
    Lewis, Suzanna E.
    Thomas, Paul D.
    Sonnhammer, Erik
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Dessimoz, Christophe
    Standardized benchmarking in the quest for orthologs2016In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 13, no 5, 425-+ p.Article in journal (Refereed)
    Abstract [en]

    Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

  • 2. Branca, Rui M. M.
    et al.
    Orre, Lukas M.
    Johansson, Henrik J.
    Granholm, Viktor
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Huss, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Perez-Bercoff, Åsa
    Forshed, Jenny
    Käll, Lukas
    Lehtio, Janne
    HiRIEF LC-MSMS enables deep proteome coverage and unbiased proteogenomics2014In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 11, no 1, 59-+ p.Article in journal (Refereed)
    Abstract [en]

    We present a liquid chromatography-mass spectrometry (LC-MSMS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectively. The method also enabled deep proteome coverage, identifying 13,078 human and 10,637 mouse proteins.

  • 3. Fuller, Franklin D.
    et al.
    Gul, Sheraz
    Chatterjee, Ruchira
    Burgie, E. Sethe
    Young, Iris D.
    Lebrette, Hugo
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Srinivas, Vivek
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Brewster, Aaron S.
    Michels-Clark, Tara
    Clinger, Jonathan A.
    Andi, Babak
    Ibrahim, Mohamed
    Pastor, Ernest
    de Lichtenberg, Casper
    Hussein, Rana
    Pollock, Christopher J.
    Zhang, Miao
    Stan, Claudiu A.
    Kroll, Thomas
    Fransson, Thomas
    Weninger, Clemens
    Kubin, Markus
    Aller, Pierre
    Lassalle, Louise
    Bräuer, Philipp
    Miller, Mitchell D.
    Amin, Muhamed
    Koroidov, Sergey
    Roessler, Christian G.
    Allaire, Marc
    Sierra, Raymond G.
    Docker, Peter T.
    Glownia, James M.
    Nelson, Silke
    Koglin, Jason E.
    Zhu, Diling
    Chollet, Matthieu
    Song, Sanghoon
    Lemke, Henrik
    Liang, Mengning
    Sokaras, Dimosthenis
    Alonso-Mori, Roberto
    Zouni, Athina
    Messinger, Johannes
    Bergmann, Uwe
    Boal, Amie K.
    Bollinger, J. Martin
    Krebs, Carsten
    Högbom, Martin
    Phillips, George N.
    Vierstra, Richard D.
    Sauter, Nicholas K.
    Orville, Allen M.
    Kern, Jan
    Yachandra, Vittal K.
    Yano, Junko
    Drop-on-demand sample delivery for studying biocatalysts in action at X-ray free-electron lasers2017In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 14, no 4, 443-449 p.Article in journal (Refereed)
    Abstract [en]

    X-ray crystallography at X-ray free-electron laser sources is a powerful method for studying macromolecules at biologically relevant temperatures. Moreover, when combined with complementary techniques like X-ray emission spectroscopy, both global structures and chemical properties of metalloenzymes can be obtained concurrently, providing insights into the interplay between the protein structure and dynamics and the chemistry at an active site. The implementation of such a multimodal approach can be compromised by conflicting requirements to optimize each individual method. In particular, the method used for sample delivery greatly affects the data quality. We present here a robust way of delivering controlled sample amounts on demand using acoustic droplet ejection coupled with a conveyor belt drive that is optimized for crystallography and spectroscopy measurements of photochemical and chemical reactions over a wide range of time scales. Studies with photosystem IIII, the phytochrome photoreceptor, and ribonucleotide reductase R2 illustrate the power and versatility of this method.

  • 4. Hattne, Johan
    et al.
    Echols, Nathaniel
    Tran, Rosalie
    Kern, Jan
    Gildea, Richard J.
    Brewster, Aaron S.
    Alonso-Mori, Roberto
    Gloeckner, Carina
    Hellmich, Julia
    Laksmono, Hartawan
    Sierra, Raymond G.
    Lassalle-Kaiser, Benedikt
    Lampe, Alyssa
    Han, Guangye
    Gul, Sheraz
    DiFiore, Doerte
    Milathianaki, Despina
    Fry, Alan R.
    Miahnahri, Alan
    White, William E.
    Schafer, Donald W.
    Seibert, M. Marvin
    Koglin, Jason E.
    Sokaras, Dimosthenis
    Weng, Tsu-Chien
    Sellberg, Jonas
    Stockholm University, Faculty of Science, Department of Physics. SLAC National Accelerator Laboratory, USA.
    Latimers, Matthew J.
    Glatzel, Pieter
    Zwart, Petrus H.
    Grosse-Kunstleve, Ralf W.
    Bogan, Michael J.
    Messerschmidt, Marc
    Williams, Garth J.
    Boutet, Sebastien
    Messinger, Johannes
    Zouni, Athina
    Yano, Junko
    Bergmann, Uwe
    Yachandra, Vittal K.
    Adams, Paul D.
    Sauter, Nicholas K.
    Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers2014In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 11, no 5, 545-548 p.Article in journal (Refereed)
    Abstract [en]

    X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

  • 5.
    Ke, Rongqin
    et al.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Uppsala University .
    Mignardi, Marco
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Uppsala University .
    Pacureanu, Alexandra
    Svedlund, Jessica
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Botling, Johan
    Wählby, Carolina
    Nilsson, Mats
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Uppsala University.
    In situ sequencing for RNA analysis in preserved tissue and cells2013In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 10, no 9, 857-+ p.Article in journal (Refereed)
    Abstract [en]

    Tissue gene expression profiling is performed on homogenates or on populations of isolated single cells to resolve molecular states of different cell types. In both approaches, histological context is lost. We have developed an in situ sequencing method for parallel targeted analysis of short RNA fragments in morphologically preserved cells and tissue. We demonstrate in situ sequencing of point mutations and multiplexed gene expression profiling in human breast cancer tissue sections.

  • 6. Nordahl Petersen, Thomas
    et al.
    Brunak, Soren
    von Heijne, Gunnar
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Nielsen, Henrik
    SignalP 4.0: discriminating signal peptides from transmembrane regions2011In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 8, no 10, 785-786 p.Article in journal (Refereed)
  • 7.
    Oliveberg, Mikael
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Waltz, an exciting new move in amyloid prediction2010In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 7, no 3, 187-8 p.Article in journal (Refereed)
  • 8. Persson, Fredrik
    et al.
    Lindén, Martin
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
    Unoson, Cecilia
    Elf, Johan
    Extracting intracellular diffusive states and transition rates from single-molecule tracking data2013In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 10, no 3, 265-269 p.Article in journal (Refereed)
    Abstract [en]

    We provide an analytical tool based on a variational Bayesian treatment of hidden Markov models to combine the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the number of diffusive states and the state transition rates. Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs and their mRNA targets.

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