F. C. Garton et al., “Whole exome sequencing and DNA methylation analysis in a clinical amyotrophic lateral sclerosis cohort,” Molecular Genetics &; Genomic Medicine, vol. 5, no. 4. Wiley, pp. 418–428, 2017.

L. R. Lloyd-Jones et al., “Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models,” Genetics, vol. 206, no. 2. Genetics Society of America, pp. 1113–1126, 2017.

J. P. Sethna et al., “Deformation of crystals: Connections with statistical physics,” Annual Review of Materials Research, vol. 47. Annual Reviews, pp. 217–246, 2017.

J. W. Rocks, N. Pashine, I. Bischofberger, C. P. Goodrich, A. J. Liu, and S. R. Nagel, “Designing allostery-inspired response in mechanical networks,” Proceedings of the National Academy of Sciences, vol. 114, no. 10. Proceedings of the National Academy of Sciences, pp. 2520–2525, 2017.

C. P. Goodrich and M. P. Brenner, “Using active colloids as machines to weave and braid on the micrometer scale,” Proceedings of the National Academy of Sciences, vol. 114, no. 2. Proceedings of the National Academy of Sciences, pp. 257–262, 2017.

M. Baity-Jesi, C. P. Goodrich, A. J. Liu, S. R. Nagel, and J. P. Sethna, “Emergent SO(3) symmetry of the frictionless shear jamming transition,” Journal of Statistical Physics, vol. 167, no. 3–4. Springer Nature, pp. 735–748, 2017.

D.-A. Alistarh, B. Dudek, A. Kosowski, D. Soloveichik, and P. Uznaski, “Robust detection in leak-prone population protocols,” presented at the DNA Computing and Molecular Programming, 2017, vol. 10467 LNCS, pp. 155–171.

D.-A. Alistarh, J. Aspnes, D. Eisenstat, R. Rivest, and R. Gelashvili, “Time-space trade-offs in population protocols,” presented at the SODA: Symposium on Discrete Algorithms, 2017, pp. 2560–2579.

D.-A. Alistarh, W. Leiserson, A. Matveev, and N. Shavit, “Forkscan: Conservative memory reclamation for modern operating systems,” presented at the EuroSys: European Conference on Computer Systems, 2017, pp. 483–498.

K. Kara, D.-A. Alistarh, G. Alonso, O. Mutlu, and C. Zhang, “FPGA-accelerated dense linear machine learning: A precision-convergence trade-off,” presented at the FCCM: Field-Programmable Custom Computing Machines, 2017, pp. 160–167.

R. Fulek, J. Kyndl, and D. Pálvölgyi, “Unified Hanani Tutte theorem,” Electronic Journal of Combinatorics, vol. 24, no. 3. International Press, 2017.

L. Schafzahl et al., “Singulett-Sauerstoff in der aprotischen Natrium-O2-Batterie,” Angewandte Chemie, vol. 129, no. 49. Wiley, pp. 15934–15938, 2017.

S. Yee Liew, W. Thielemans, S. A. Freunberger, and S. Spirk, “Polysaccharides in supercapacitors,” in Polysaccharide Based Supercapacitors, S. Yee Liew, W. Thielemans, S. A. Freunberger, and S. Spirk, Eds. Springer Nature, 2017, pp. 15–53.

S. A. Freunberger, “True performance metrics in beyond-intercalation batteries,” Nature Energy, vol. 2, no. 7. Springer Nature, 2017.

N. Mahne et al., “Singlet oxygen generation as a major cause for parasitic reactions during cycling of aprotic lithium–oxygen batteries,” Nature Energy, vol. 2, no. 5. Springer Nature, 2017.

J. M. Fink, “Photonenblockade aufgelöst,” Physik in unserer Zeit, vol. 48, no. 3. Wiley, pp. 111–113, 2017.

R. P. Costa, Z. Padamsey, J. A. D’Amour, N. J. Emptage, R. C. Froemke, and T. P. Vogels, “Synaptic transmission optimization predicts expression loci of long-term plasticity,” Neuron, vol. 96, no. 1. Elsevier, p. 177–189.e7, 2017.

H. C. Barron, T. P. Vogels, T. E. Behrens, and M. Ramaswami, “Inhibitory engrams in perception and memory,” Proceedings of the National Academy of Sciences, vol. 114, no. 26. Proceedings of the National Academy of Sciences, pp. 6666–6674, 2017.

T. P. Vogels and L. C. Griffith, “Editorial overview: Neurobiology of learning and plasticity 2017,” Current Opinion in Neurobiology, vol. 43. Elsevier, pp. –, 2017.

G. Hennequin, E. J. Agnes, and T. P. Vogels, “Inhibitory plasticity: Balance, control, and codependence,” Annual Review of Neuroscience, vol. 40, no. 1. Annual Reviews, pp. 557–579, 2017.