Zibrov, A., Rao, P., Kometter, C., Li, J., Dean, C., Taniguchi, T.,https://doi.org/10.1103/PhysRevLett.121.167601__Young, A. (2018). Emergent dirac gullies and gully-symmetry-breaking quantum hall states in ABA trilayer graphene. Physical Review Letters. American Physical Society.https://doi.org/10.1103/PhysRevLett.121.167601 

Salari, V., Barzanjeh, S., Cifra, M., Simon, C., Scholkmann, F., Alirezaei, Z., &; Tuszynski, J. (2018). Electromagnetic fields and optomechanics In cancer diagnostics and treatment. Frontiers in Bioscience - Landmark. Frontiers in Bioscience.https://doi.org/10.2741/4651 

Matousek, J., Sedgwick, E., Tancer, M., &; Wagner, U. (2018). Embeddability in the 3-Sphere is decidable. Journal of the ACM. ACM.https://doi.org/10.1145/3078632 

Barton, N. H., &; Etheridge, A. (2018). Establishment in a new habitat by polygenic adaptation. Theoretical Population Biology. Academic Press.https://doi.org/10.1016/j.tpb.2017.11.007 

Hilbe, C., Simsa, S., Chatterjee, K., &; Nowak, M. (2018). Evolution of cooperation in stochastic games. Nature. Nature Publishing Group.https://doi.org/10.1038/s41586-018-0277-x 

Hönigschmid, P., Bykova, N., Schneider, R., Ivankov, D., &; Frishman, D. (2018). Evolutionary interplay between symbiotic relationships and patterns of signal peptide gain and loss. Genome Biology and Evolution. Oxford University Press.https://doi.org/10.1093/gbe/evy049 

Ringbauer, H., Kolesnikov, A., Field, D., &; Barton, N. H. (2018). Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.117.300638 

Sato, T., Wojtan, C., Thuerey, N., Igarashi, T., &; Ando, R. (2018). Extended narrow band FLIP for liquid simulations. Computer Graphics Forum. Wiley.https://doi.org/10.1111/cgf.13351 

Bodova, K., Priklopil, T., Field, D., Barton, N. H., &; Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.118.300748 

Harrison, M., Arning, N., Kremer, L., Ylla, G., Belles, X., Bornberg Bauer, E.,https://doi.org/10.1002/jez.b.22824__Schal, C. (2018). Expansions of key protein families in the German cockroach highlight the molecular basis of its remarkable success as a global indoor pest. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution. Wiley.https://doi.org/10.1002/jez.b.22824 

Fischer, J. L., &; Grün, G. (2018). Existence of positive solutions to stochastic thin-film equations. SIAM Journal on Mathematical Analysis. Society for Industrial and Applied Mathematics .https://doi.org/10.1137/16M1098796 

Bodova, K., Priklopil, T., Field, D., Barton, N. H., &; Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America.https://doi.org/10.25386/genetics.6148304.v1 

Kotlobay, A. A., Sarkisyan, K., Mokrushina, Y. A., Marcet-Houben, M., Serebrovskaya, E. O., Markina, N. M.,https://doi.org/10.1073/pnas.1803615115__Yampolsky, I. V. (2018). Genetically encodable bioluminescent system from fungi. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences.https://doi.org/10.1073/pnas.1803615115 

Salanenka, Y., Verstraeten, I., Löfke, C., Tabata, K., Naramoto, S., Glanc, M., &; Friml, J. (2018). Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1721760115 

Shabazi, A., Kinnison, J., Vescovi, R., Du, M., Hill, R., Jösch, M. A.,https://doi.org/10.1038/s41598-018-32628-3__Scheirer, W. (2018). Flexible learning-free segmentation and reconstruction of neural volumes. Scientific Reports. Nature Publishing Group.https://doi.org/10.1038/s41598-018-32628-3 

Leithner, A. F., Renkawitz, J., de Vries, I., Hauschild, R., Haecker, H., &; Sixt, M. K. (2018). Fast and efficient genetic engineering of hematopoietic precursor cells for the study of dendritic cell migration. European Journal of Immunology. Wiley-Blackwell.https://doi.org/10.1002/eji.201747358 

Kutzer, M., Kurtz, J., &; Armitage, S. (2018). Genotype and diet affect resistance, survival, and fecundity but not fecundity tolerance. Journal of Evolutionary Biology. Wiley.https://doi.org/10.1111/jeb.13211 

Tarlungeanu, D.-C., &; Novarino, G. (2018). Genomics in neurodevelopmental disorders: an avenue to personalized medicine. Experimental &; Molecular Medicine. Springer Nature.https://doi.org/10.1038/s12276-018-0129-7 

Lundholm, D., &; Seiringer, R. (2018). Fermionic behavior of ideal anyons. Letters in Mathematical Physics. Springer.https://doi.org/10.1007/s11005-018-1091-y 

Richter, R., Baranova, N. S., Day, A., &; Kwok, J. (2018). Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets? Current Opinion in Structural Biology. Elsevier.https://doi.org/10.1016/j.sbi.2017.12.002 

Harrison, M., Jongepier, E., Robertson, H., Arning, N., Bitard Feildel, T., Chao, H.,https://doi.org/10.1038/s41559-017-0459-1__Bornberg Bauer, E. (2018). Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature Ecology and Evolution. Springer Nature.https://doi.org/10.1038/s41559-017-0459-1 

Oliveto, P., Paixao, T., Pérez Heredia, J., Sudholt, D., &; Trubenova, B. (2018). How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. Springer.https://doi.org/10.1007/s00453-017-0369-2 

Darrell, T., Lampert, C., Sebe, N., Wu, Y., &; Yan, Y. (2018). Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE.https://doi.org/10.1109/TPAMI.2018.2804998 

Harrison, M. C., Jongepier, E., Robertson, H. M., Arning, N., Bitard-Feildel, T., Chao, H.,https://doi.org/10.5061/dryad.51d4r__Bornberg-Bauer, E. (2018). Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality. Dryad.https://doi.org/10.5061/dryad.51d4r 

Chen, T., Kula, B., Nagy, B., Barzan, R., Gall, A., Ehrlich, I., &; Kukley, M. (2018). In Vivo regulation of Oligodendrocyte processor cell proliferation and differentiation by the AMPA-receptor Subunit Glu. Cell Reports. Elsevier.https://doi.org/10.1016/j.celrep.2018.09.066 

Reversat, A., &; Sixt, M. K. (2018). IgM’s exit route. Journal of Experimental Medicine. Rockefeller University Press.https://doi.org/10.1084/jem.20181934 

Akopyan, A., &; Bobenko, A. (2018). Incircular nets and confocal conics. Transactions of the American Mathematical Society. American Mathematical Society.https://doi.org/10.1090/tran/7292 

Avni, G., Henzinger, T. A., &; Ibsen-Jensen, R. (2018). Infinite-duration poorman-bidding games (Vol. 11316, pp. 21–36). Presented at the 14th International Conference on Web and Internet Economics, WINE, Oxford, UK: Springer.https://doi.org/10.1007/978-3-030-04612-5_2 

Dick, R., Zadrozny, K. K., Xu, C., Schur, F. K., Lyddon, T. D., Ricana, C. L.,https://doi.org/10.1038/s41586-018-0396-4__Vogt, V. (2018). Inositol phosphates are assembly co-factors for HIV-1. Nature. Nature Publishing Group.https://doi.org/10.1038/s41586-018-0396-4 

Kalinin, N., &; Shkolnikov, M. (2018). Introduction to tropical series and wave dynamic on them. Discrete and Continuous Dynamical Systems- Series A. AIMS.https://doi.org/10.3934/dcds.2018120 

Locatello, F., Dresdner, G., Khanna, R., Valera, I., &; Rätsch, G. (2018). Boosting black box variational inference. In Advances in Neural Information Processing Systems (Vol. 31). Montreal, Canada: Neural Information Processing Systems Foundation.

Locatello, F., Khanna, R., Ghosh, J., &; Rätsch, G. (2018). Boosting variational inference: An optimization perspective. In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (Vol. 84, pp. 464–472). Playa Blanca, Lanzarote: ML Research Press.

Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., &; Rätsch, G. (2018). SOM-VAE: Interpretable discrete representation learning on time series. In International Conference on Learning Representations. New Orleans, LA, United States.

Yurtsever, A., Fercoq, O., Locatello, F., &; Cevher, V. (2018). A conditional gradient framework for composite convex minimization with applications to semidefinite programming. In Proceedings of the 35th International Conference on Machine Learning (Vol. 80, pp. 5727–5736). Stockholm, Sweden: ML Research Press.

Sachdeva, H., &; Barton, N. H. (2018). Introgression of a block of genome under infinitesimal selection. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.118.301018 

Obremski, M., &; Skórski, M. (2018). Inverted leftover hash lemma (Vol. 2018). Presented at the ISIT: International Symposium on Information Theory, Vail, CO, USA: IEEE.https://doi.org/10.1109/ISIT.2018.8437654 

Locatello, F., Raj, A., Karimireddy, S. P., Rätsch, G., Schölkopf, B., Stich, S. U., &; Jaggi, M. (2018). On matching pursuit and coordinate descent. In Proceedings of the 35th International Conference on Machine Learning (Vol. 80, pp. 3198–3207). ML Research Press.

Kragl, B., &; Qadeer, S. (2018). Layered Concurrent Programs (Vol. 10981, pp. 79–102). Presented at the CAV: Computer Aided Verification, Oxford, UK: Springer.https://doi.org/10.1007/978-3-319-96145-3_5 

Chaudhry, W., Pleska, M., Shah, N., Weiss, H., Mccall, I., Meyer, J.,https://doi.org/10.1371/journal.pbio.2005971__Levin, B. (2018). Leaky resistance and the conditions for the existence of lytic bacteriophage. PLoS Biology. Public Library of Science.https://doi.org/10.1371/journal.pbio.2005971 

Umetani, N., &; Bickel, B. (2018). Learning three-dimensional flow for interactive aerodynamic design. ACM Trans. Graph. ACM.https://doi.org/10.1145/3197517.3201325 

Alt, J., Erdös, L., &; Krüger, T. H. (2018). Local inhomogeneous circular law. Annals Applied Probability . Institute of Mathematical Statistics.https://doi.org/10.1214/17-AAP1302 

Akopyan, A., &; Petrunin, A. (2018). Long geodesics on convex surfaces. Mathematical Intelligencer. Springer.https://doi.org/10.1007/s00283-018-9795-5 

Brown, M., Johnson, L., Leone, D., Májek, P., Vaahtomeri, K., Senfter, D.,https://doi.org/10.1083/jcb.201612051__Kerjaschki, D. (2018). Lymphatic exosomes promote dendritic cell migration along guidance cues. Journal of Cell Biology. Rockefeller University Press.https://doi.org/10.1083/jcb.201612051 

Robert, H., Park, C., Gutièrrez, C., Wójcikowska, B., Pbndík, A., Novák, O.,https://doi.org/10.1038/s41477-018-0204-z__Laux, T. (2018). Maternal auxin supply contributes to early embryo patterning in Arabidopsis. Nature Plants. Nature Publishing Group.https://doi.org/10.1038/s41477-018-0204-z 

Fiedorczuk, K., &; Sazanov, L. A. (2018). Mammalian mitochondrial complex I structure and disease causing mutations. Trends in Cell Biology. Elsevier.https://doi.org/10.1016/j.tcb.2018.06.006 

Chatterjee, K., Dvorák, W., Henzinger, M. H., &; Loitzenbauer, V. (2018). Lower bounds for symbolic computation on graphs: Strongly connected components, liveness, safety, and diameter (pp. 2341–2356). Presented at the SODA: Symposium on Discrete Algorithms, New Orleans, Louisiana, United States: ACM.https://doi.org/10.1137/1.9781611975031.151 

Barzanjeh, S., Aquilina, M., &; Xuereb, A. (2018). Manipulating the flow of thermal noise in quantum devices. Physical Review Letters. American Physical Society.https://doi.org/10.1103/PhysRevLett.120.060601 

Hross, S., Theis, F. J., Sixt, M. K., &; Hasenauer, J. (2018). Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data. Journal of the Royal Society Interface. Royal Society Publishing.https://doi.org/10.1098/rsif.2018.0600 

Varshney, A., &; Steinberg, V. (2018). Mixing layer instability and vorticity amplification in a creeping viscoelastic flow. Physical Review Fluids. American Physical Society.https://doi.org/10.1103/PhysRevFluids.3.103303 

Rybicki, J., Kisdi, E., &; Anttila, J. (2018). Model of bacterial toxin-dependent pathogenesis explains infective dose. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1721061115