Experts and Thought Leaders in Statistics

Engineering Analysis with Boundary Elements / Jul 01, 2002

Hernandez, J. P., Raush, T., Rios, A., Strauss, S., & Osswald, T. A. (2002). Analysis of fiber damage mechanisms during processing of reinforced polymer melts. Engineering Analysis with Boundary Elements, 26(7), 621–628. https://doi.org/10.1016/s0955-7997(02)00018-8

Journal of Fluency Disorders / Jun 01, 2015

Obituary. (2015). Journal of Fluency Disorders, 44, 96. https://doi.org/10.1016/s0094-730x(15)00047-9

International Journal of Business Intelligence Research / Jul 01, 2010

Park, J., Fables, W., Parker, K. R., & Nitse, P. S. (2010). The Role of Culture in Business Intelligence. International Journal of Business Intelligence Research, 1(3), 1–14. https://doi.org/10.4018/jbir.2010070101

Journal of the Medical Library Association / Dec 08, 2022

Gaffney, S. G., & Townsend, J. P. (2022). Jot: guiding journal selection with suitability metrics. Journal of the Medical Library Association, 110(3), 376–380. https://doi.org/10.5195/jmla.2022.1499

Bioinformatics / Aug 08, 2016

Gaffney, S. G., & Townsend, J. P. (2016). PathScore: a web tool for identifying altered pathways in cancer data. Bioinformatics, 32(23), 3688–3690. https://doi.org/10.1093/bioinformatics/btw512

Statistical Applications in Genetics and Molecular Biology / Jan 01, 2015

Ghosh, S., & Townsend, J. P. (2015). H-CLAP: hierarchical clustering within a linear array with an application in genetics. Statistical Applications in Genetics and Molecular Biology, 14(2). https://doi.org/10.1515/sagmb-2013-0076

Bioinformatics / Jun 03, 2013

Dai, L., Tian, M., Wu, J., Xiao, J., Wang, X., Townsend, J. P., & Zhang, Z. (2013). AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification. Bioinformatics, 29(14), 1837–1839. https://doi.org/10.1093/bioinformatics/btt284

Bioinformatics / Jun 10, 2010

Zhang, Z., López-Giráldez, F., & Townsend, J. P. (2010). LOX: inferring Level Of eXpression from diverse methods of census sequencing. Bioinformatics, 26(15), 1918–1919. https://doi.org/10.1093/bioinformatics/btq303

Journal of Biomedical Informatics / Oct 01, 2008

Cheung, K.-H., Yip, K. Y., Townsend, J. P., & Scotch, M. (2008). HCLS 2.0/3.0: Health care and life sciences data mashup using Web 2.0/3.0. Journal of Biomedical Informatics, 41(5), 694–705. https://doi.org/10.1016/j.jbi.2008.04.001

Cognitive Computation / Aug 17, 2017

Li, Y., Pan, Q., Yang, T., Wang, S., Tang, J., & Cambria, E. (2017). Learning Word Representations for Sentiment Analysis. Cognitive Computation, 9(6), 843–851. https://doi.org/10.1007/s12559-017-9492-2

Neurocomputing / Feb 01, 2015

Peng, Y., Wang, S., Long, X., & Lu, B.-L. (2015). Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing, 149, 340–353. https://doi.org/10.1016/j.neucom.2013.12.065

Neural Networks / May 01, 2015

Peng, Y., Lu, B.-L., & Wang, S. (2015). Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks, 65, 1–17. https://doi.org/10.1016/j.neunet.2015.01.001

Neurocomputing / Oct 01, 2020

Li, Y., Wang, S., Ma, Y., Pan, Q., & Cambria, E. (2020). Popularity prediction on vacation rental websites. Neurocomputing, 412, 372–380. https://doi.org/10.1016/j.neucom.2020.05.092

Healthcare / Aug 27, 2021

Ali, G. G. Md. N., Rahman, Md. M., Hossain, Md. A., Rahman, Md. S., Paul, K. C., Thill, J.-C., & Samuel, J. (2021). Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics. Healthcare, 9(9), 1110. https://doi.org/10.3390/healthcare9091110

Trends in Cognitive Sciences / Feb 01, 2005

Steinberg, L. (2005). Cognitive and affective development in adolescence. Trends in Cognitive Sciences, 9(2), 69–74. https://doi.org/10.1016/j.tics.2004.12.005

Developmental Science / Dec 15, 2010

Chein, J., Albert, D., O’Brien, L., Uckert, K., & Steinberg, L. (2010). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Developmental Science, 14(2), F1–F10. https://doi.org/10.1111/j.1467-7687.2010.01035.x

Developmental Cognitive Neuroscience / Feb 01, 2016

Shulman, E. P., Smith, A. R., Silva, K., Icenogle, G., Duell, N., Chein, J., & Steinberg, L. (2016). The dual systems model: Review, reappraisal, and reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117. https://doi.org/10.1016/j.dcn.2015.12.010

Brain and Cognition / Feb 01, 2010

Steinberg, L. (2010). A behavioral scientist looks at the science of adolescent brain development. Brain and Cognition, 72(1), 160–164. https://doi.org/10.1016/j.bandc.2009.11.003

Developmental Science / Feb 01, 2017

Steinberg, L., Icenogle, G., Shulman, E. P., Breiner, K., Chein, J., Bacchini, D., Chang, L., Chaudhary, N., Giunta, L. D., Dodge, K. A., Fanti, K. A., Lansford, J. E., Malone, P. S., Oburu, P., Pastorelli, C., Skinner, A. T., Sorbring, E., Tapanya, S., Tirado, L. M. U., … Takash, H. M. S. (2017). Around the world, adolescence is a time of heightened sensation seeking and immature self-regulation. Developmental Science, 21(2), e12532. Portico. https://doi.org/10.1111/desc.12532

Journal of the American Statistical Association / Jul 02, 2016

Roberts, M. E., Stewart, B. M., & Airoldi, E. M. (2016). A Model of Text for Experimentation in the Social Sciences. Journal of the American Statistical Association, 111(515), 988–1003. https://doi.org/10.1080/01621459.2016.1141684

Biometrika / Apr 17, 2012

Choi, D. S., Wolfe, P. J., & Airoldi, E. M. (2012). Stochastic blockmodels with a growing number of classes. Biometrika, 99(2), 273–284. https://doi.org/10.1093/biomet/asr053

Bioinformatics / Jan 22, 2015

Katz, Y., Wang, E. T., Silterra, J., Schwartz, S., Wong, B., Thorvaldsdóttir, H., Robinson, J. T., Mesirov, J. P., Airoldi, E. M., & Burge, C. B. (2015). Quantitative visualization of alternative exon expression from RNA-seq data. Bioinformatics, 31(14), 2400–2402. https://doi.org/10.1093/bioinformatics/btv034

Journal of the American Statistical Association / Jun 30, 2020

Forastiere, L., Airoldi, E. M., & Mealli, F. (2020). Identification and Estimation of Treatment and Interference Effects in Observational Studies on Networks. Journal of the American Statistical Association, 116(534), 901–918. https://doi.org/10.1080/01621459.2020.1768100

The Annals of Statistics / Aug 01, 2017

Toulis, P., & Airoldi, E. M. (2017). Asymptotic and finite-sample properties of estimators based on stochastic gradients. The Annals of Statistics, 45(4). https://doi.org/10.1214/16-aos1506

Journal of the American Statistical Association / Oct 01, 2016

Airoldi, E. M., & Bischof, J. M. (2016). Improving and Evaluating Topic Models and Other Models of Text. Journal of the American Statistical Association, 111(516), 1381–1403. https://doi.org/10.1080/01621459.2015.1051182

Biometrika / Aug 06, 2018

Basse, G. W., & Airoldi, E. M. (2018). Model-assisted design of experiments in the presence of network-correlated outcomes. Biometrika, 105(4), 849–858. https://doi.org/10.1093/biomet/asy036

Statistics in Medicine / Jan 01, 2017

Lunceford, J. K. (2017). Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study. Statistics in Medicine. Portico. https://doi.org/10.1002/sim.7231

Journal of the Royal Statistical Society: Series B (Statistical Methodology) / Dec 09, 2020

Toulis, P., Horel, T., & Airoldi, E. M. (2020). The proximal Robbins–Monro method. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 83(1), 188–212. Portico. https://doi.org/10.1111/rssb.12405

Biometrika / Sep 30, 2019

Pouget-Abadie, J., Saint-Jacques, G., Saveski, M., Duan, W., Ghosh, S., Xu, Y., & Airoldi, E. M. (2019). Testing for arbitrary interference on experimentation platforms. Biometrika, 106(4), 929–940. https://doi.org/10.1093/biomet/asz047

Journal of the American Statistical Association / Jan 02, 2017

Lunagómez, S., Mukherjee, S., Wolpert, R. L., & Airoldi, E. M. (2017). Geometric Representations of Random Hypergraphs. Journal of the American Statistical Association, 112(517), 363–383. https://doi.org/10.1080/01621459.2016.1141686

Journal of Medical Internet Research / Oct 30, 2020

Janmohamed, K., Soale, A.-N., Forastiere, L., Tang, W., Sha, Y., Demant, J., Airoldi, E., & Kumar, N. (2020). Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study. Journal of Medical Internet Research, 22(10), e21743. https://doi.org/10.2196/21743

Statistics and Computing / Jun 11, 2015

Toulis, P., & Airoldi, E. M. (2015). Scalable estimation strategies based on stochastic approximations: classical results and new insights. Statistics and Computing, 25(4), 781–795. https://doi.org/10.1007/s11222-015-9560-y

Journal of the American Statistical Association / Jan 02, 2015

Franks, A. M., Csárdi, G., Drummond, D. A., & Airoldi, E. M. (2015). Estimating a Structured Covariance Matrix From Multilab Measurements in High-Throughput Biology. Journal of the American Statistical Association, 110(509), 27–44. https://doi.org/10.1080/01621459.2014.964404

Journal of the American Statistical Association / Oct 02, 2014

Airoldi, E. M., Costa, T., Bassetti, F., Leisen, F., & Guindani, M. (2014). Generalized Species Sampling Priors With Latent Beta Reinforcements. Journal of the American Statistical Association, 109(508), 1466–1480. https://doi.org/10.1080/01621459.2014.950735

Journal of the American Statistical Association / Mar 01, 2013

Airoldi, E. M., & Blocker, A. W. (2013). Estimating Latent Processes on a Network From Indirect Measurements. Journal of the American Statistical Association, 108(501), 149–164. https://doi.org/10.1080/01621459.2012.756328

The Annals of Applied Statistics / Dec 01, 2013

Airoldi, E. M., Wang, X., & Lin, X. (2013). Multi-way blockmodels for analyzing coordinated high-dimensional responses. The Annals of Applied Statistics, 7(4). https://doi.org/10.1214/13-aoas643

Statistical Analysis and Data Mining / Sep 09, 2011

Airoldi, E. M., Choi, D. S., & Wolfe, P. J. (2011). Confidence sets for network structure. Statistical Analysis and Data Mining, 4(5), 461–469. https://doi.org/10.1002/sam.10136

The Annals of Applied Statistics / Jun 01, 2010

Silva, R., Heller, K., Ghahramani, Z., & Airoldi, E. M. (2010). Ranking relations using analogies in biological and information networks. The Annals of Applied Statistics, 4(2). https://doi.org/10.1214/09-aoas321

Bayesian Analysis / Jun 01, 2006

Airoldi, E. M., Anderson, A. G., Fienberg, S. E., & Skinner, K. K. (2006). Who wrote Ronald Reagan’s radio addresses? Bayesian Analysis, 1(2). https://doi.org/10.1214/06-ba110

Journal of Applied Statistics / Nov 14, 2018

Fernández, D., Harel, D., Ipeirotis, P., & McAllister, T. (2018). Statistical considerations for crowdsourced perceptual ratings of human speech productions. Journal of Applied Statistics, 46(8), 1364–1384. https://doi.org/10.1080/02664763.2018.1547692

ACM Transactions on Economics and Computation / Mar 27, 2015

Leyton-Brown, K., & Ipeirotis, P. (Eds.). (2015). Introduction to the Special Issue on EC’12. ACM Transactions on Economics and Computation, 3(1), 1–2. https://doi.org/10.1145/2742678

JMIR Medical Informatics / Jun 02, 2021

Makridis, C., Hurley, S., Klote, M., & Alterovitz, G. (2021). Ethical Applications of Artificial Intelligence: Evidence From Health Research on Veterans. JMIR Medical Informatics, 9(6), e28921. https://doi.org/10.2196/28921

Computers in Biology and Medicine / Jun 01, 2021

Makridis, C. A., Zhao, D. Y., Bejan, C. A., & Alterovitz, G. (2021). Leveraging machine learning to characterize the role of socio-economic determinants on physical health and well-being among veterans. Computers in Biology and Medicine, 133, 104354. https://doi.org/10.1016/j.compbiomed.2021.104354

BMJ Health & Care Informatics / Jun 01, 2021

Makridis, C. A., Strebel, T., Marconi, V., & Alterovitz, G. (2021). Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs. BMJ Health & Care Informatics, 28(1), e100312. https://doi.org/10.1136/bmjhci-2020-100312

Cerebral Cortex / Jan 19, 2017

Cottereau, B. R., Smith, A. T., Rima, S., Fize, D., Héjja-Brichard, Y., Renaud, L., Lejards, C., Vayssière, N., Trotter, Y., & Durand, J.-B. (2017). Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex. Cerebral Cortex. https://doi.org/10.1093/cercor/bhw412

Cerebral Cortex / Oct 17, 2020

De Castro, V., Smith, A. T., Beer, A. L., Leguen, C., Vayssière, N., Héjja-Brichard, Y., Audurier, P., Cottereau, B. R., & Durand, J. B. (2020). Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys. Cerebral Cortex, 31(2), 1347–1364. https://doi.org/10.1093/cercor/bhaa301

Cerebral Cortex / Mar 28, 2020

Héjja-Brichard, Y., Rima, S., Rapha, E., Durand, J.-B., & Cottereau, B. R. (2020). Stereomotion Processing in the Nonhuman Primate Brain. Cerebral Cortex, 30(8), 4528–4543. https://doi.org/10.1093/cercor/bhaa055

NeuroImage / Aug 01, 2022

Niso, G., Krol, L. R., Combrisson, E., Dubarry, A. S., Elliott, M. A., François, C., Héjja-Brichard, Y., Herbst, S. K., Jerbi, K., Kovic, V., Lehongre, K., Luck, S. J., Mercier, M., Mosher, J. C., Pavlov, Y. G., Puce, A., Schettino, A., Schön, D., Sinnott-Armstrong, W., … Chaumon, M. (2022). Good scientific practice in EEG and MEG research: Progress and perspectives. NeuroImage, 257, 119056. https://doi.org/10.1016/j.neuroimage.2022.119056

Cerebral Cortex / Oct 06, 2021

Audurier, P., Héjja-Brichard, Y., De Castro, V., Kohler, P. J., Norcia, A. M., Durand, J.-B., & Cottereau, B. R. (2021). Symmetry Processing in the Macaque Visual Cortex. Cerebral Cortex, 32(10), 2277–2290. https://doi.org/10.1093/cercor/bhab358

The Journal of Business / Apr 01, 2003

Abarbanell, J. S., Bushee, B. J., & Smith Raedy, J. (2003). Institutional Investor Preferences and Price Pressure: The Case of Corporate Spin‐Offs*. The Journal of Business, 76(2), 233–261. https://doi.org/10.1086/367749

Insurance: Mathematics and Economics / Nov 01, 2013

Zhang, H., Leung, T., & Hadjiliadis, O. (2013). Stochastic modeling and fair valuation of drawdown insurance. Insurance: Mathematics and Economics, 53(3), 840–850. https://doi.org/10.1016/j.insmatheco.2013.10.006

Risk and Decision Analysis / Jan 01, 2014

Leung, T., Li, X., & Wang, Z. (2014). Optimal starting–stopping and switching of a CIR process with fixed costs. Risk and Decision Analysis, 5(2–3), 149–161. https://doi.org/10.3233/rda-140107

Risk and Decision Analysis / May 31, 2017

Leung, T., & Li, Z. (2017). Timing options for a startup with early termination and competition risks. Risk and Decision Analysis, 6(2), 151–166. https://doi.org/10.3233/rda-170120

SIAM Journal on Financial Mathematics / Jan 01, 2015

Leung, T., & Wan, H. (2015). ESO Valuation with Job Termination Risk and Jumps in Stock Price. SIAM Journal on Financial Mathematics, 6(1), 487–516. https://doi.org/10.1137/130937949

Stochastic Models / Jul 16, 2015

Leung, T., Li, X., & Wang, Z. (2015). Optimal Multiple Trading Times Under the Exponential OU Model with Transaction Costs. Stochastic Models, 31(4), 554–587. https://doi.org/10.1080/15326349.2015.1058717

Stochastic Processes and their Applications / Feb 01, 2013

Egami, M., Leung, T., & Yamazaki, K. (2013). Default swap games driven by spectrally negative Lévy processes. Stochastic Processes and Their Applications, 123(2), 347–384. https://doi.org/10.1016/j.spa.2012.09.008

Finance and Stochastics / Aug 27, 2013

Leung, T., Song, Q., & Yang, J. (2013). Outperformance portfolio optimization via the equivalence of pure and randomized hypothesis testing. Finance and Stochastics, 17(4), 839–870. https://doi.org/10.1007/s00780-013-0213-8

Mathematics and Financial Economics / Feb 24, 2012

Leung, T., & Ludkovski, M. (2012). Accounting for risk aversion in derivatives purchase timing. Mathematics and Financial Economics, 6(4), 363–386. https://doi.org/10.1007/s11579-012-0063-8

Stochastics / Jun 19, 2012

Leung, T., Sircar, R., & Zariphopoulou, T. (2012). Forward indifference valuation of American options. Stochastics, 84(5–6), 741–770. https://doi.org/10.1080/17442508.2012.694438

SIAM Journal on Financial Mathematics / Jan 01, 2011

Leung, T., & Ludkovski, M. (2011). Optimal Timing to Purchase Options. SIAM Journal on Financial Mathematics, 2(1), 768–793. https://doi.org/10.1137/100809386

SIAM Journal on Financial Mathematics / Jan 01, 2017

Huang, Y. T., Zeng, P., & Kwok, Y. K. (2017). Optimal Initiation of Guaranteed Lifelong Withdrawal Benefit with Dynamic Withdrawals. SIAM Journal on Financial Mathematics, 8(1), 804–840. https://doi.org/10.1137/16m1089575

International Journal of Risk Assessment and Management / Jan 01, 2007

Stahl, B. C. (2007). Reflective responsibility for risk: a critical view of software and information systems development risk management. International Journal of Risk Assessment and Management, 7(3), 312. https://doi.org/10.1504/ijram.2007.011985

Physica A: Statistical Mechanics and its Applications / Feb 01, 2019

Kutner, R., Ausloos, M., Grech, D., Di Matteo, T., Schinckus, C., & Eugene Stanley, H. (2019). Econophysics and sociophysics: Their milestones & challenges. Physica A: Statistical Mechanics and Its Applications, 516, 240–253. https://doi.org/10.1016/j.physa.2018.10.019

Physica A: Statistical Mechanics and its Applications / Oct 01, 2009

Schinckus, C. (2009). Economic uncertainty and econophysics. Physica A: Statistical Mechanics and Its Applications, 388(20), 4415–4423. https://doi.org/10.1016/j.physa.2009.07.008

Physica A: Statistical Mechanics and its Applications / Sep 01, 2010

Schinckus, C. (2010). Is econophysics a new discipline? The neopositivist argument. Physica A: Statistical Mechanics and Its Applications, 389(18), 3814–3821. https://doi.org/10.1016/j.physa.2010.05.016

Physica A: Statistical Mechanics and its Applications / Dec 01, 2020

Ausloos, M., Grech, D., Di Matteo, T., Kutner, R., Schinckus, C., & Stanley, H. E. (2020). Manifesto for a post-pandemic modeling. Physica A: Statistical Mechanics and Its Applications, 559, 125086. https://doi.org/10.1016/j.physa.2020.125086

Physica A: Statistical Mechanics and its Applications / Jan 01, 2019

Ausloos, M., Grech, D., Di Matteo, T., Kutner, R., Schinckus, C., & Stanley, H. E. (2019). Preface. Physica A: Statistical Mechanics and Its Applications, 513, 272. https://doi.org/10.1016/j.physa.2018.08.173

Physica A: Statistical Mechanics and its Applications / Mar 01, 2018

Schinckus, C., Altukhov, Y. A., & Pokrovskii, V. N. (2018). Empirical justification of the elementary model of money circulation. Physica A: Statistical Mechanics and Its Applications, 493, 228–238. https://doi.org/10.1016/j.physa.2017.10.054

Physica A: Statistical Mechanics and its Applications / Oct 01, 2018

Schinckus, C. (2018). Ising model, econophysics and analogies. Physica A: Statistical Mechanics and Its Applications, 508, 95–103. https://doi.org/10.1016/j.physa.2018.05.063

Physica A: Statistical Mechanics and its Applications / Dec 01, 2016

Pokrovskii, V. N., & Schinckus, C. (2016). An elementary model of money circulation. Physica A: Statistical Mechanics and Its Applications, 463, 111–122. https://doi.org/10.1016/j.physa.2016.07.006

Physica A: Statistical Mechanics and its Applications / Sep 01, 2013

Schinckus, C. (2013). Between complexity of modelling and modelling of complexity: An essay on econophysics. Physica A: Statistical Mechanics and Its Applications, 392(17), 3654–3665. https://doi.org/10.1016/j.physa.2013.04.005

Physica A: Statistical Mechanics and its Applications / Oct 01, 2011

Bucsa, G., Jovanovic, F., & Schinckus, C. (2011). A unified model for price return distributions used in econophysics. Physica A: Statistical Mechanics and Its Applications, 390(20), 3435–3443. https://doi.org/10.1016/j.physa.2011.04.012

Discrete & Continuous Dynamical Systems - A / Jan 01, 2003

D. Emerson, N. (2003). Dynamics of polynomials with disconnected Julia sets. Discrete & Continuous Dynamical Systems - A, 9(4), 801–834. https://doi.org/10.3934/dcds.2003.9.801

Statistical Science / May 01, 2006

Ghose, A., & Sundararajan, A. (2006). Evaluating Pricing Strategy Using e-Commerce Data: Evidence and Estimation Challenges. Statistical Science, 21(2). https://doi.org/10.1214/088342306000000187

Trends in Cognitive Sciences / Nov 01, 2022

Regan, A., Radošić, N., & Lyubomirsky, S. (2022). Experimental effects of social behavior on well-being. Trends in Cognitive Sciences, 26(11), 987–998. https://doi.org/10.1016/j.tics.2022.08.006

Journal of Medical Internet Research / Jun 08, 2019

Sanders, C. A., Schueller, S. M., Parks, A. C., & Howell, R. T. (2019). Understanding Long-Term Trajectories in Web-Based Happiness Interventions: Secondary Analysis From Two Web-Based Randomized Trials. Journal of Medical Internet Research, 21(6), e13253. https://doi.org/10.2196/13253

Computers in Human Behavior Reports / Aug 01, 2022

Okabe-Miyamoto, K., Durnell, E., Howell, R. T., & Zizi, M. (2022). Video conferencing during emergency distance learning impacted student emotions during COVID-19. Computers in Human Behavior Reports, 7, 100199. https://doi.org/10.1016/j.chbr.2022.100199

NeuroQuantology / Sep 12, 2007

McFadden, J. (2007). Conscious Electromagnetic (CEMI) Field Theory. NeuroQuantology, 5(3). https://doi.org/10.14704/nq.2007.5.3.135

Biosystems / Jun 01, 1999

McFadden, J., & Al-Khalili, J. (1999). A quantum mechanical model of adaptive mutation. Biosystems, 50(3), 203–211. https://doi.org/10.1016/s0303-2647(99)00004-0

Quantum Reports / Jan 26, 2021

Kim, Y., Bertagna, F., D’Souza, E. M., Heyes, D. J., Johannissen, L. O., Nery, E. T., Pantelias, A., Sanchez-Pedreño Jimenez, A., Slocombe, L., Spencer, M. G., Al-Khalili, J., Engel, G. S., Hay, S., Hingley-Wilson, S. M., Jeevaratnam, K., Jones, A. R., Kattnig, D. R., Lewis, R., Sacchi, M., … McFadden, J. (2021). Quantum Biology: An Update and Perspective. Quantum Reports, 3(1), 80–126. https://doi.org/10.3390/quantum3010006

Journal of Theoretical Biology / Jun 01, 1997

McFadden, J., & Knowles, G. (1997). Escape From Evolutionary Stasis by Transposon-mediated Deleterious Mutations. Journal of Theoretical Biology, 186(4), 441–447. https://doi.org/10.1006/jtbi.1997.0403

Healthcare / Jan 04, 2023

Sulaiteen, F. M., Al-Zaagi, I. A., Alenazi, M. S., Alotaibi, A. Z., Alghamdi, T. A., Yousaf, A., & Ali, S. (2023). Awareness of Cardiovascular Disease Risk Factors by Community Pharmacists in Saudi Arabia. Healthcare, 11(2), 151. https://doi.org/10.3390/healthcare11020151

Neuropsychologia / Sep 01, 2014

Rossi, E., Kroll, J. F., & Dussias, P. E. (2014). Clitic pronouns reveal the time course of processing gender and number in a second language. Neuropsychologia, 62, 11–25. https://doi.org/10.1016/j.neuropsychologia.2014.07.002

Language, Cognition and Neuroscience / Aug 19, 2016

Contemori, C., & Dussias, P. E. (2016). Referential choice in a second language: evidence for a listener-oriented approach. Language, Cognition and Neuroscience, 31(10), 1257–1272. https://doi.org/10.1080/23273798.2016.1220604

Journal of Neurolinguistics / Feb 01, 2021

Rossi, E., Dussias, P. E., Diaz, M., van Hell, J. G., & Newman, S. (2021). Neural signatures of inhibitory control in intra-sentential code-switching: Evidence from fMRI. Journal of Neurolinguistics, 57, 100938. https://doi.org/10.1016/j.jneuroling.2020.100938

Psychophysiology / Dec 02, 2020

Beatty‐Martínez, A. L., Bruni, M. R., Bajo, M. T., & Dussias, P. E. (2020). Brain potentials reveal differential processing of masculine and feminine grammatical gender in native Spanish speakers. Psychophysiology, 58(3). Portico. https://doi.org/10.1111/psyp.13737

Language, Cognition and Neuroscience / Aug 03, 2022

Navarro-Torres, C. A., Dussias, P. E., & Kroll, J. F. (2022). When exceptions matter: bilinguals regulate their dominant language to exploit structural constraints in sentence production. Language, Cognition and Neuroscience, 38(2), 217–242. https://doi.org/10.1080/23273798.2022.2105915

Visual Cognition / Aug 01, 2013

Cain, M. S., Adamo, S. H., & Mitroff, S. R. (2013). A taxonomy of errors in multiple-target visual search. Visual Cognition, 21(7), 899–921. https://doi.org/10.1080/13506285.2013.843627

Cognitive Research: Principles and Implications / Jun 14, 2018

Adamo, S. H., Ericson, J. M., Nah, J. C., Brem, R., & Mitroff, S. R. (2018). Mammography to tomosynthesis: examining the differences between two-dimensional and segmented-three-dimensional visual search. Cognitive Research: Principles and Implications, 3(1). https://doi.org/10.1186/s41235-018-0103-x

Visual Cognition / Aug 09, 2015

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