SynaptomeDB: an ontology-based knowledgebase for synaptic genes

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works

Gene Ontology: tool for the unification of biology

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works

The Protein Data Bank

Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · see citing works

Molecular signatures database (MSigDB) 3.0

Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr260 · Cited by 7,111 · see citing works

Human Protein Reference Database--2009 update

Prasad, T. S. K., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, R. B., Venugopal, A., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn892 · Cited by 3,241 · see citing works

STRING: a database of predicted functional associations between proteins

von Mering, C. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg034 · Cited by 2,942 · see citing works

Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database

Bertram, L., McQueen, M. B., Mullin, K., Blacker, D., & Tanzi, R. E. (2007) · Nature Genetics · doi:10.1038/ng1934 · Cited by 1,857 · see citing works

A new bioinformatics analysis tools framework at EMBL-EBI

Goujon, M., McWilliam, H., Li, W., Valentin, F., Squizzato, S., Paern, J., & Lopez, R. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq313 · Cited by 1,846 · see citing works

The Bioperl Toolkit: Perl Modules for the Life SciencesPreprint

Stajich, J., Block, D., Boulez, K., Brenner, S. E., Chervitz, S. A., Dagdigian, C., Fuellen, G., Gilbert, J. G. R., Korf, I. F., Lapp, H., et al. (2002) · Genome Research · doi:10.1101/gr.361602 · Cited by 1,642 · see citing works

Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder

Wellcome Trust Case Control Consortium, Ferreira, M. A. R., O'Donovan, M. C., Meng, Y. A., Jones, I. R., Ruderfer, D. M., Jones, L., Fan, J., Kirov, G., Perlis, R. H., et al. (2008) · Nature Genetics · doi:10.1038/ng.209 · Cited by 1,237 · see citing works

Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database

Allen, N. C., Bagade, S., McQueen, M. B., Ioannidis, J. P. A., Kavvoura, F. K., Khoury, M. J., Tanzi, R. E., & Bertram, L. (2008) · Nature Genetics · doi:10.1038/ng.171 · Cited by 1,054 · see citing works

Ensembl 2011

Flicek, P., Amode, M. R., Barrell, D. G., Beal, K. M., Brent, S., Chen, Y., Clapham, P., Coates, G. M. P., Fairley, S., Fitzgerald, S. F., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1064 · Cited by 596 · see citing works

To build a synapse: signaling pathways in neuromuscular junction assembly

Wu, H., Xiong, W., & Mei, L. (2010) · Development · doi:10.1242/dev.038711 · Cited by 519 · see citing works

bioDBnet: the biological database network

Mudunuri, U. S., Che, A., Yi, M., & Stephens, R. M. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btn654 · Cited by 366 · see citing works

Novel de novo SHANK3 mutation in autistic patients

Gauthier, J., Spiegelman, D., Piton, A., Lafrenière, R. G., Laurent, S., St‐Onge, J., Lapointe, L., Hamdan, F. F., Cossette, P., Mottron, L., et al. (2009) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30822 · Cited by 321 · see citing works

Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies

Shyn, S. I., Shi, J., Kraft, J. B., Potash, J. B., Knowles, J. A., Weissman, M. M., Garriock, H. A., Yokoyama, J. S., McGrath, P. J., Peters, E. J., et al. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.125 · Cited by 270 · see citing works

Strong synaptic transmission impact by copy number variations in schizophrenia

Glessner, J., Reilly, M. P., Kim, C., Takahashi, N., Albano, A., Hou, C., Bradfield, J. P., Zhang, H., Abou‐Sleiman, P. M., Flory, J. H., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000274107 · Cited by 231 · see citing works

The architecture of an excitatory synapse

Chua, J. J. E., Kindler, S., Boyken, J., & Jahn, R. (2010) · Journal of Cell Science · doi:10.1242/jcs.052696 · Cited by 114 · see citing works

Overlapping Probabilities of Top Ranking Gene Lists, Hypergeometric Distribution, and Stringency of Gene Selection Criterion

Fury, W., Batliwalla, F., Gregersen, P. K., & Li, W. (2006) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2006.260828 · Cited by 114 · see citing works

Statistical Methods for Pathway Analysis of Genome-Wide Data for Association with Complex Genetic Traits

Holmans, P. (2010) · Advances in genetics · doi:10.1016/b978-0-12-380862-2.00007-2 · Cited by 99 · see citing works

Systems approach to explore components and interactions in the presynapse

Abul‐Husn, N. S., Bushlin, I., Morón, J. A., Jenkins, S. L., Dolios, G., Wang, R., Iyengar, R., Ma'ayan, A., & Devi, L. A. (2009) · PROTEOMICS · doi:10.1002/pmic.200800767 · Cited by 53 · see citing works

SynDB: a Synapse protein DataBase based on synapse ontology

Zhang, W., Zhang, Y., Zheng, H., Zhang, C., Xiong, W., Olyarchuk, J. G., Walker, M., Xu, W., Zhao, M., Zhao, S., et al. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl876 · Cited by 47 · see citing works

Association study of PDE4B gene variants in scandinavian schizophrenia and bipolar disorder multicenter case–control samples

Kähler, A. K., Otnæss, M. K., Wirgenes, K. V., Hansen, T. F., Jönsson, E. G., Agartz, I., Hall, H., Werge, T. M., Morken, G., Mors, O. N., et al. (2009) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30958 · Cited by 39 · see citing works

GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments

Kirov, S., Peng, X., Baker, E. J., Schmoyer, D. D., Zhang, B., & Snoddy, J. R. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-72 · Cited by 19 · see citing works

Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography

Burt, J. B., Demirtaş, M., Eckner, W. J., Navejar, N. M., Ji, J. L., Martin, W. J., Bernacchia, A., Anticevic, A., & Murray, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0195-0 · Cited by 657 · see citing works

Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia

Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444 · see citing works

Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes

Zhou, X., Feliciano, P., Shu, C., Wang, T., Astrovskaya, I., Hall, J. B., Obiajulu, J. U., Wright, J. R., Murali, S. C., Xu, S. X., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01148-2 · Cited by 453 · see citing works

Proteomic Analysis of Unbounded Cellular Compartments: Synaptic Clefts

Loh, K. H., Stawski, P. S., Draycott, A. S., Udeshi, N. D., Lehrman, E. K., Wilton, D. K., Svinkina, T., Deerinck, T. J., Ellisman, M. H., Stevens, B., et al. (2016) · Cell · doi:10.1016/j.cell.2016.07.041 · Cited by 399 · see citing works

A comprehensive transcriptional map of primate brain development

Bakken, T. E., Miller, J. A., Ding, S., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Dalley, R. A., Royall, J. J., Lemon, T. A., et al. (2016) · Nature · doi:10.1038/nature18637 · Cited by 376 · see citing works

Precisely measured protein lifetimes in the mouse brain reveal differences across tissues and subcellular fractions

Fornasiero, E. F., Mandad, S., Wildhagen, H., Alevra, M., Rammner, B., Keihani, S., Opazo, F., Urban, I., Ischebeck, T., Sakib, M. S., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06519-0 · Cited by 340 · see citing works

Global Transcriptional and Translational Repression in Human-Embryonic-Stem-Cell-Derived Rett Syndrome Neurons

Li, Y., Wang, H., Muffat, J., Cheng, A. W., Orlando, D. A., Lovén, J., Kwok, S., Feldman, D., Bateup, H. S., Gao, Q., et al. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.09.001 · Cited by 305 · see citing works

Novel Alzheimer risk genes determine the microglia response to amyloid-β but not to TAU pathology

Sierksma, A., Lu, A., Mancuso, R., Fattorelli, N., Thrupp, N., Salta, E., Zoco, J., Blum, D., Buée, L., De Strooper, B., et al. (2020) · EMBO Molecular Medicine · doi:10.15252/emmm.201910606 · Cited by 291 · see citing works

MEF2C regulates cortical inhibitory and excitatory synapses and behaviors relevant to neurodevelopmental disorders

Harrington, A. J., Raissi, A., Rajkovich, K., Berto, S., Kumar, J., Molinaro, G., Raduazzo, J., Guo, Y., Loerwald, K., Konopka, G., et al. (2016) · eLife · doi:10.7554/elife.20059 · Cited by 193 · see citing works

Hotspots of missense mutation identify neurodevelopmental disorder genes and functional domains

Geisheker, M. R., Heymann, G., Wang, T., Coe, B. P., Turner, T. N., Stessman, H. A. F., Hoekzema, K., Kvarnung, M., Shaw, M. A., Friend, K. L., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4589 · Cited by 175 · see citing works

Integrated systems analysis reveals a molecular network underlying autism spectrum disorders

Li, J., Shi, M., Ma, Z., Zhao, S., Euskirchen, G., Ziskin, J., Urban, A., Hallmayer, J., & Snyder, M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145487 · Cited by 132 · see citing works

Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism

Urresti, J., Zhang, P., Losada, P. M., Yu, N., Negraes, P. D., Trujillo, C. A., Antaki, D., Amar, M., Chau, K. K., Pramod, A. B., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01243-6 · Cited by 133 · see citing works

A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data

Wang, Q., Chen, R., Cheng, F., Wei, Q., Ji, Y., Hai, Y., Zhong, X. Y., Tao, R., Wen, Z., Sutcliffe, J. S., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0382-7 · Cited by 130 · see citing works

De Novo Synonymous Mutations in Regulatory Elements Contribute to the Genetic Etiology of Autism and Schizophrenia

Takata, A., Ionita‐Laza, I., Gogos, J. A., Xu, B., & Karayiorgou, M. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.024 · Cited by 126 · see citing works

Autism-Misregulated eIF4G Microexons Control Synaptic Translation and Higher Order Cognitive Functions

Gonatopoulos-Pournatzis, T., Niibori, R., Salter, E. W., Weatheritt, R. J., Tsang, B., Farhangmehr, S., Liang, X., Braunschweig, U., Roth, J. F., Zhang, S., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.01.006 · Cited by 119 · see citing works

In vivo brain GPCR signaling elucidated by phosphoproteomics

Liu, J. J., Sharma, K., Zangrandi, L., Chen, C., Humphrey, S. J., Chiu, Y.-T., Spetea, M., Liu‐Chen, L., Schwarzer, C., & Mann, M. (2018) · Science · doi:10.1126/science.aao4927 · Cited by 118 · see citing works

Locus Coeruleus and Dopamine-Dependent Memory Consolidation

Yamasaki, M., & Takeuchi, T. (2017) · Neural Plasticity · doi:10.1155/2017/8602690 · Cited by 91 · see citing works

Olfactory bulb neuroproteomics reveals a chronological perturbation of survival routes and a disruption of prohibitin complex during Alzheimer’s disease progression

Lachén‐Montes, M., González-Morales, A., Zelaya, M. V., Pérez‐Valderrama, E., Ausín, K., Ferrer, I., Fernández‐Irigoyen, J., & Santamaría, E. (2017) · Scientific Reports · doi:10.1038/s41598-017-09481-x · Cited by 95 · see citing works

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders

Nguyen, H. T., Bryois, J., Kim, A., Dobbyn, A. L., Huckins, L. M., Muñoz‐Manchado, A. B., Ruderfer, D. M., Genovese, G., Fromer, M., Xu, X., et al. (2017) · Genome Medicine · doi:10.1186/s13073-017-0497-y · Cited by 86 · see citing works

ELAVL2-regulated transcriptional and splicing networks in human neurons link neurodevelopment and autism

Berto, S., Usui, N., Konopka, G., & Fogel, B. L. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw110 · Cited by 80 · see citing works

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Dear, R., Wagstyl, K., Seidlitz, J., Markello, R. D., Arnatkevičiūtė, A., Anderson, K. M., Bethlehem, R. A. I., Raznahan, A., Bullmore, E. T., & Vértes, P. E. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01624-4 · Cited by 83 · see citing works

Proteomics of the Synapse – A Quantitative Approach to Neuronal Plasticity

Dieterich, D. C., & Kreutz, M. R. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r115.051482 · Cited by 73 · see citing works

iTRAQ-based quantitative analysis of hippocampal postsynaptic density-associated proteins in a rat chronic mild stress model of depression

Han, X., Shao, W., Liu, Z., Fan, S., Yu, J. H., Chen, J., Qiao, R., Zhou, J., & Xie, P. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.04.006 · Cited by 71 · see citing works

Transgenic rhesus monkeys carrying the human MCPH1 gene copies show human-like neoteny of brain development

Shi, L., Luo, X., Jiang, J., Chen, Y., Liu, C., Hu, T., Li, M., Lin, Q., Li, Y., Huang, J. T., et al. (2019) · National Science Review · doi:10.1093/nsr/nwz043 · Cited by 70 · see citing works

Synaptic proteins associated with cognitive performance and neuropathology in older humans revealed by multiplexed fractionated proteomics

Carlyle, B. C., Kandigian, S. E., Kreuzer, J., Das, S., Trombetta, B. A., Kuo, Y., Bennett, D. A., Schneider, J. A., Petyuk, V. A., Kitchen, R. R., et al. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.04.012 · Cited by 65 · see citing works

MECP2 directly interacts with RNA polymerase II to modulate transcription in human neurons

Liu, Y., Flamier, A., Bell, G. W., Diao, A. J., Whitfield, T. W., Wang, H., Wu, Y., Schulte, F., Friesen, M., Guo, R., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.007 · Cited by 62 · see citing works

Stress-induced Changes in the S-palmitoylation and S-nitrosylation of Synaptic Proteins*[S]

Zaręba-Kozioł, M., Bartkowiak-Kaczmarek, A., Figiel, I., Krzystyniak, A., Wójtowicz, T., Bijata, M., & Włodarczyk, J. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra119.001581 · Cited by 58 · see citing works

Leveraging blood serotonin as an endophenotype to identify de novo and rare variants involved in autism

Chen, R., Davis, L. K., Guter, S. J., Wei, Q., Jacob, S., Potter, M. H., Cox, N. J., Cook, E. H., Sutcliffe, J. S., & Li, B. (2017) · Molecular Autism · doi:10.1186/s13229-017-0130-3 · Cited by 57 · see citing works

Estrogen activates Alzheimer's disease genes

Ratnakumar, A., Zimmerman, S. E., Jordan, B. A., & Mar, J. C. (2019) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2019.09.004 · Cited by 52 · see citing works

SynSysNet: integration of experimental data on synaptic protein–protein interactions with drug-target relations

von Eichborn, J., Dunkel, M., Gohlke, B.-O., Preissner, S. C., Hoffmann, M. F., Bauer, J. M. J., Armstrong, J. D., Schaefer, M. H., Andrade-Navarro, M. A., Novère, N. G. L., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1040 · Cited by 52 · see citing works

Dynamic Control of Synaptic Adhesion and Organizing Molecules in Synaptic Plasticity

Rudenko, G. (2017) · Neural Plasticity · doi:10.1155/2017/6526151 · Cited by 52 · see citing works

The conserved microRNA miR-34 regulates synaptogenesis via coordination of distinct mechanisms in presynaptic and postsynaptic cells

McNeill, E. M., Warinner, C. B., Alkins, S., Taylor, A., Heggeness, H., DeLuca, T. F., Fulga, T. A., Wall, D. P., Griffith, L. C., & Vactor, D. V. (2020) · Nature Communications · doi:10.1038/s41467-020-14761-8 · Cited by 47 · see citing works

Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signaling

Amar, M., Pramod, A. B., Yu, N., Herrera, V. M., Qiu, L. R., Losada, P. M., Zhang, P., Trujillo, C. A., Ellegood, J., Urresti, J., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01052-x · Cited by 50 · see citing works

Proteomic comparison of different synaptosome preparation procedures

Gulyássy, P., Puska, G., Györffy, B. A., Völgyi, K., Juhász, G. D., Drahos, L., & Kékesi, K. A. (2020) · Amino Acids · doi:10.1007/s00726-020-02912-6 · Cited by 49 · see citing works

Neuron-specific transcriptomic signatures indicate neuroinflammation and altered neuronal activity in ASD temporal cortex

Zhang, P., Omanska-Klusek, A., Ander, B. P., Gandal, M. J., Stamova, B. S., & Schumann, C. M. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2206758120 · Cited by 46 · see citing works

Full-length isoform transcriptome of the developing human brain provides further insights into autism

Chau, K. K., Zhang, P., Urresti, J., Amar, M., Pramod, A. B., Chen, J., Thomas, A. E., Corominas, R., Lin, G. N., & Iakoucheva, L. M. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109631 · Cited by 42 · see citing works

Disruption of NEUROD2 causes a neurodevelopmental syndrome with autistic features via cell-autonomous defects in forebrain glutamatergic neurons

Runge, K., Mathieu, R., Bugeon, S., Lafi, S., Beurrier, C., Sahu, S., Schaller, F., Loubat, A., Hérault, L., Gaillard, S., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01179-x · Cited by 47 · see citing works

Global analysis of S-nitrosylation sites in the wild type (APP) transgenic mouse brain: Clues for synaptic pathology

Zaręba-Kozioł, M., Szwajda, A., Dadlez, M., Wysłouch-Cieszyńska, A., & Lalowski, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.036079 · Cited by 39 · see citing works

Burden of Rare Variants in Synaptic Genes in Patients with Severe Tinnitus: An Exome Based Extreme Phenotype Study

Amanat, S., Gallego‐Martinez, A., Sollini, J., Perez‐Carpena, P., Espinosa-Sánchez, J. M., Arán, I., Soto-Varela, A., Caletrío, Á. B., Canlon, B., May, P., et al. (2020) · EBioMedicine · doi:10.1016/j.ebiom.2021.103309 · Cited by 39 · see citing works

Synaptic proteomics reveal distinct molecular signatures of cognitive change and C9ORF72 repeat expansion in the human ALS cortex

László, Z. I., Hindley, N., Avila, A. S., Kline, R., Eaton, S. L., Lamont, D. J., Smith, C., Spires‐Jones, T. L., Wishart, T. M., & Henstridge, C. M. (2022) · Acta Neuropathologica Communications · doi:10.1186/s40478-022-01455-z · Cited by 38 · see citing works

Temporal lobe proteins implicated in synaptic failure exhibit differential expression and deamidation in vascular dementia

Gallart‐Palau, X., Serra, A., Qian, J., Chen, C., Kalaria, R. N., & Sze, S. K. (2014) · Neurochemistry International · doi:10.1016/j.neuint.2014.12.002 · Cited by 36 · see citing works

A single-cell genomic atlas for maturation of the human cerebellum during early childhood

Ament, S. A., Cortes-Gutierrez, M., Herb, B. R., Mocci, E., Colantuoni, C., & McCarthy, M. M. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.ade1283 · Cited by 34 · see citing works

Quantitative Proteomic Analysis Reveals Molecular Adaptations in the Hippocampal Synaptic Active Zone of Chronic Mild Stress-Unsusceptible Rats

Zhou, J., Liu, Z., Yu, J. H., Han, X., Fan, S., Shao, W., Chen, J., Qiao, R., & Xie, P. (2015) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyv100 · Cited by 31 · see citing works

Neurexins — versatile molecular platforms in the synaptic cleft

Rudenko, G. (2019) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2019.01.009 · Cited by 31 · see citing works

Combined glyoxalase 1 dysfunction and vitamin B6 deficiency in a schizophrenia model system causes mitochondrial dysfunction in the prefrontal cortex

Toriumi, K., Berto, S., Koike, S., Usui, N., Dan, T., Suzuki, K., Miyashita, M., Horiuchi, Y., Yoshikawa, A., Asakura, M., et al. (2021) · Redox Biology · doi:10.1016/j.redox.2021.102057 · Cited by 31 · see citing works

Novel transcriptional networks regulated by CLOCK in human neuronsPreprint

Fontenot, M. R., Berto, S., Liu, Y., Werthmann, G. C., Douglas, C., Usui, N., Gleason, K., Tamminga, C. A., Takahashi, J. S., & Konopka, G. (2017) · Genes & Development · doi:10.1101/gad.305813.117 · Cited by 30 · see citing works

High-throughput sequencing of the synaptome in major depressive disorder

Pirooznia, M., Wang, T., Avramopoulos, D., Potash, J. B., Zandi, P. P., & Goes, F. S. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.98 · Cited by 29 · see citing works

Systematic Review of Sequencing Studies and Gene Expression Profiling in Familial Meniere Disease

Escalera‐Balsera, A., Román-Naranjo, P., & Lopez-Escamez, J. A. (2020) · Genes · doi:10.3390/genes11121414 · Cited by 28 · see citing works

Novel ultra-rare exonic variants identified in a founder population implicate cadherins in schizophrenia

Lencz, T., Yu, J., Khan, R. R., Flaherty, E. K., Carmi, S., Lam, M., Ben‐Avraham, D., Barzilai, N., Bressman, S., Darvasi, A., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.004 · Cited by 29 · see citing works

Postnatal Tshz3 Deletion Drives Altered Corticostriatal Function and Autism Spectrum Disorder–like Behavior

Chabbert, D., Caubit, X., Roubertoux, P. L., Carlier, M., Habermann, B. H., Jacq, B., Salin, P., Metwaly, M., Frahm, C., Fatmi, A., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.03.974 · Cited by 28 · see citing works

Microglial TNFα orchestrates protein phosphorylation in the cortex during the sleep period and controls homeostatic sleep

Pinto, M. J., Cottin, L., Dingli, F., Laigle, V., Ribeiro, L. F., Triller, A., Henderson, F., Loew, D., Fabre, V., & Bessis, A. (2022) · The EMBO Journal · doi:10.15252/embj.2022111485 · Cited by 24 · see citing works

Identifying rare genetic variants in 21 highly multiplex autism families: the role of diagnosis and autistic traits

More, R. P., Warrier, V., Brunel, H., Buckingham, C., Smith, P. L., Allison, C. L., Holt, R., Bradshaw, C. R., & Baron‐Cohen, S. (2023) · Molecular Psychiatry · doi:10.1038/s41380-022-01938-4 · Cited by 26 · see citing works

Weighted Burden Analysis of Exome-Sequenced Case-Control Sample Implicates Synaptic Genes in Schizophrenia Aetiology

Curtis, D., Coelewij, L., Liu, S.-H., Humphrey, J., & Mott, R. (2018) · Behavior Genetics · doi:10.1007/s10519-018-9893-3 · Cited by 25 · see citing works

A Hybrid Likelihood Model for Sequence-Based Disease Association Studies

Chen, Y.-C., Carter, H. K., Parla, J. S., Kramer, M., Goes, F. S., Pirooznia, M., Zandi, P. P., McCombie, W. R., Potash, J. B., & Karchin, R. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003224 · Cited by 24 · see citing works

Compensation between FOXP transcription factors maintains proper striatal function

Ahmed, N. I., Khandelwal, N., Anderson, A. G., Oh, E., Vollmer, R. M., Kulkarni, A., Gibson, J. R., & Konopka, G. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114257 · Cited by 22 · see citing works

Exome-wide analysis of mutational burden in patients with typical and atypical Rolandic epilepsy

Bobbili, D. R., Lal, D., May, P., Reinthaler, E. M., Jabbari, K., Thiele, H., Nothnagel, M., Jurkowski, W., Feucht, M., Nürnberg, P., et al. (2018) · European Journal of Human Genetics · doi:10.1038/s41431-017-0034-x · Cited by 23 · see citing works

A weighted burden test using logistic regression for integrated analysis of sequence variants, copy number variants and polygenic risk score

Curtis, D. (2018) · European Journal of Human Genetics · doi:10.1038/s41431-018-0272-6 · Cited by 22 · see citing works

iTRAQ-Based Quantitative Proteomics Suggests Synaptic Mitochondrial Dysfunction in the Hippocampus of Rats Susceptible to Chronic Mild Stress

Xie, H., Huang, H., Tang, M., Wu, Y., Huang, R., Liu, Z., Zhou, M., Liao, W., & Zhou, J. (2018) · Neurochemical Research · doi:10.1007/s11064-018-2664-y · Cited by 22 · see citing works

Integrative proteomics highlight presynaptic alterations and c-Jun misactivation as convergent pathomechanisms in ALS

Aly, A., Laszlo, Z. I., Rajkumar, S., Demir, T., Hindley, N., Lamont, D. J., Lehmann, J., Seidel, M., Sommer, D., Franz-Wachtel, M., et al. (2023) · Acta Neuropathologica · doi:10.1007/s00401-023-02611-y · Cited by 21 · see citing works

Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach

Obregón, F. P., Papalardo, C., Castro, S., Guerberoff, G., & Cantera, R. (2015) · BMC Genomics · doi:10.1186/s12864-015-1888-3 · Cited by 21 · see citing works

The Retinal Ganglion Cell Transportome Identifies Proteins Transported to Axons and Presynaptic Compartments in the Visual System In Vivo

Schiapparelli, L., Shah, S. H., Ma, Y., McClatchy, D. B., Sharma, P., Li, J., Yates, J. R., Goldberg, J. L., & Cline, H. T. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.037 · Cited by 21 · see citing works

Proteomic screen reveals diverse protein transport between connected neurons in the visual system

Schiapparelli, L., Sharma, P., He, H., Li, J., Shah, S. H., McClatchy, D. B., Ma, Y., Liu, H.-H., Goldberg, J. L., Yates, J. R., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110287 · Cited by 20 · see citing works

Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

He, D., Fan, C., Qi, M., Yang, Y., Cooper, D. N., & Zhao, H. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01294-x · Cited by 19 · see citing works

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disordersPreprint

Nguyen, H. T., Bryois, J., Kim, A., Dobbyn, A., Huckins, L. M., Muñoz‐Manchado, A. B., Ruderfer, D. M., Genovese, G., Fromer, M., Xu, X., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/135293 · Cited by 19 · see citing works

Distinct gene-set burden patterns underlie common generalized and focal epilepsies

Koko, M., Krause, R., Sander, T., Bobbili, D. R., Nothnagel, M., May, P., Lerche, H., Feng, Y. A., Howrigan, D. P., Abbott, L. E., et al. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103588 · Cited by 18 · see citing works

Single-cell proteomic landscape of the developing human brain

Wu, T., Jiang, L., Mukhtar, T., Wang, L., Jian, R., Wang, C., Trinh, T., Kriegstein, A. R., Snyder, M., & Li, J. (2026) · Nature Biotechnology · doi:10.1038/s41587-025-02980-7 · Cited by 23 · see citing works

Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits

Weissenkampen, J. D., Jiang, Y., Eckert, S., Jiang, B., Li, B., & Liu, D. J. (2019) · Current Protocols in Human Genetics · doi:10.1002/cphg.83 · Cited by 17 · see citing works

In-depth analysis of the synaptic plasma membrane proteome of small hippocampal slices using an integrated approach

Qiao, R., Li, S., Zhou, M., Chen, P., Liu, Z., Tang, M., & Zhou, J. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.04.015 · Cited by 16 · see citing works

Toward defining the anatomo‐proteomic puzzle of the human brain: An integrative analysis

Fernández‐Irigoyen, J., Labarga, A., Zabaleta, A., de Morentin, X. M., Pérez‐Valderrama, E., Zelaya, M. V., & Santamaría, E. (2014) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201400127 · Cited by 16 · see citing works

Neuroproteomics of the Synapse: Subcellular Quantification of Protein Networks and Signaling Dynamics

van Gelder, C. A. G. H., & Altelaar, M. A. F. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100087 · Cited by 15 · see citing works

Uncovering Discrete Synaptic Proteomes to Understand Neurological Disorders

Wang, Y., & Savas, J. N. (2018) · Proteomes · doi:10.3390/proteomes6030030 · Cited by 14 · see citing works

In the developing cerebral cortex: axonogenesis, synapse formation, and synaptic plasticity are regulated by SATB2 target genes

Guo, Q., Wang, Y., Wang, Q., Qian, Y., Jiang, Y., Dong, X., Chen, H., Chen, X., Liu, X., Yu, S., et al. (2022) · Pediatric Research · doi:10.1038/s41390-022-02260-z · Cited by 13 · see citing works

In vivo study sheds new light on the dendritic spine pathology hypothesis of schizophrenia

Li, W., Lv, L., & Luo, X. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01449-2 · Cited by 13 · see citing works

Smelling the Dark Proteome: Functional Characterization of PITH Domain-Containing Protein 1 (C1orf128) in Olfactory Metabolism

Lachén-Montes, M., Mendizuri, N., Ausín, K., Pérez-Mediavilla, A., Azkargorta, M., Iloro, I., Elortza, F., Kondo, H., Ohigashi, I., Ferrer, I., et al. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00452 · Cited by 12 · see citing works

RNA Sequencing of Creatine Transporter (SLC6A8) Deficient Fibroblasts Reveals Impairment of the Extracellular Matrix

Nota, B., Ndika, J., van de Kamp, J. M., Kanhai, W. A., van Dooren, S. J. M., van de Wiel, M. A., Pals, G., & Salomons, G. S. (2014) · Human Mutation · doi:10.1002/humu.22609 · Cited by 12 · see citing works

Neuron type-specific proteomics reveals distinct Shank3 proteoforms in iSPNs and dSPNs lead to striatal synaptopathy in Shank3B–/– mice

Wang, Y., Perez‐Rosello, T., Smukowski, S. N., Surmeier, D. J., & Savas, J. N. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02493-w · Cited by 15 · see citing works

Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies

Casella, A. M., Colantuoni, C., & Ament, S. A. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010430 · Cited by 12 · see citing works

Transcriptional control of synaptic components by the clock machinery

Hannou, L., Roy, P., Roig, M. N. B., & Mongrain, V. (2018) · European Journal of Neuroscience · doi:10.1111/ejn.14294 · Cited by 11 · see citing works

Anatomo-proteomic characterization of human basal ganglia: focus on striatum and globus pallidus

Fernández‐Irigoyen, J., Zelaya, M. V., Tuñón, T., & Santamaría, E. (2014) · Molecular Brain · doi:10.1186/s13041-014-0083-9 · Cited by 10 · see citing works

Construction of an Exome‐Wide Risk Score for Schizophrenia Based on a Weighted Burden Test

Curtis, D. (2017) · Annals of Human Genetics · doi:10.1111/ahg.12212 · Cited by 8 · see citing works

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population

Humphries, E., Ahn, K., Kember, R. L., Lopes, F. L., Mocci, E., Peralta, J. M., Blangero, J., Glahn, D. C., Goes, F. S., Zandi, P. P., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02014-1 · Cited by 9 · see citing works

Polygenic risk score for schizophrenia is not strongly associated with the expression of specific genes or gene sets

Curtis, D. (2018) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000197 · Cited by 9 · see citing works

Neurochemical and molecular characteristics of altered brain functional activity in the anti-NMDAR encephalitis

Gong, X., Li, W., Luo, C., Tian, Y., Wang, J., Gao, Y., Guo, Y., Chen, M., & Meng, Q. (2025) · Neurobiology of Disease · doi:10.1016/j.nbd.2025.107050 · Cited by 7 · see citing works

Identification of Neurotransmission and Synaptic Biological Processes Disrupted in Autism Spectrum Disorder Using Interaction Networks and Community Detection Analysis

Vilela, J. E. R., Martiniano, H., Marques, A. R., Santos, J. X., Asif, M., Rasga, C., Oliveira, G., & Vicente, A. M. (2023) · Biomedicines · doi:10.3390/biomedicines11112971 · Cited by 7 · see citing works

Occurrence of Ordered and Disordered Structural Elements in Postsynaptic Proteins Supports Optimization for Interaction Diversity

Kiss-Tóth, A., Dobson, L., Péterfia, B. F., Ángyán, A. F., Ligeti, B., Lukács, G., & Gáspári, Z. (2019) · Entropy · doi:10.3390/e21080761 · Cited by 7 · see citing works

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

Yuan, M., Gosztyla, M. L., Tan, X., Dozier, L. E., Wilkinson, B., McKetney, J., Lee, J. J. Y., Chen, M., Tsai, D. S., Kopalle, H., et al. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101204 · Cited by 6 · see citing works

Single-cell expression predicts neuron-specific protein homeostasis networks

Pechmann, S. (2024) · Open Biology · doi:10.1098/rsob.230386 · Cited by 6 · see citing works

PSINDB: the postsynaptic protein–protein interaction database

Kálmán, Z. E., Dudola, D., Mészáros, B., Gáspári, Z., & Dobson, L. (2022) · Database · doi:10.1093/database/baac007 · Cited by 6 · see citing works

Novelty-induced memory consolidation is accompanied by increased Agap3 transcription: a cross-species study

Højgaard, K., Szöllősi, B., Henningsen, K., Minami, N., Nakanishi, N., Kaadt, E., Tamura, M., Morris, R., Takeuchi, T., & Elfving, B. (2023) · Molecular Brain · doi:10.1186/s13041-023-01056-4 · Cited by 6 · see citing works

New insights into the human brain proteome: Protein expression profiling of deep brain stimulation target areas

Fernández‐Irigoyen, J., Zelaya, M. V., Pérez‐Valderrama, E., & Santamaría, E. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.03.032 · Cited by 5 · see citing works

Disruption of the transcription factor NEUROD2 causes an autism syndrome via cell-autonomous defects in cortical projection neuronsPreprint

Runge, K., Mathieu, R., Bugeon, S., Lafi, S., Beurrier, C., Sahu, S., Schaller, F., Loubat, A., Hérault, L., Gaillard, S., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/296889 · Cited by 6 · see citing works

Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism

Pirooznia, M., Niranjan, T. S., Chen, Y.-C., Tunc, I., Goes, F. S., Avramopoulos, D., Potash, J. B., Huganir, R. L., Zandi, P. P., & Wang, T. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01186 · Cited by 4 · see citing works

Multiplexed fractionated proteomics reveals synaptic factors associated with cognitive resilience in Alzheimer's DiseasePreprint

Carlyle, B. C., Kandigian, S. E., Kreuzer, J., Das, S., Trombetta, B. A., Kuo, Y., Bennett, D. A., Schneider, J. A., Petyuk, V., Kitchen, R. R., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.31.230680 · Cited by 4 · see citing works

LOCAL REGULATION AND FUNCTION OF IMPORTIN-β1 IN HIPPOCAMPAL NEURONS DURING TRANSCRIPTION-DEPENDENT PLASTICITYPreprint

Lee, Y. J., Navakkode, S., Tan, C. F., Sze, S. K., Sajikumar, S., & Ch’ng, T. H. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.02.409078 · Cited by 4 · see citing works

Three components of human brain gene expression reflect normative developmental programmes with specific links to neurodevelopmental disordersPreprint

Dear, R., Wagstyl, K., Seidlitz, J., Markello, R. D., Arnatkevičiūtė, A., Anderson, K. M., Bethlehem, R. A. I., Raznahan, A., Bullmore, E. T., & Vértes, P. E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.05.510582 · Cited by 4 · see citing works

Circadian rhythmicity and the community of clockworkers

Gamble, K. L., & Silver, R. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14626 · Cited by 3 · see citing works

The differentially expressed proteins related to clinical viral encephalitis revealed by proteomics

Wang, Q., Yan, S., Zhang, J., Du, R., Xue, L., Li, J., & Yu, C. (2022) · Ibrain · doi:10.1002/ibra.12036 · Cited by 3 · see citing works

The bewitched ear: State of the art genomics research on tinnitus

Clifford, R. E. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103349 · Cited by 3 · see citing works

Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signalingPreprint

Amar, M., Pramod, A. B., Yu, N., Herrera, V. M., Qiu, L. R., Losada, P. M., Zhang, P., Trujillo, C. A., Ellegood, J., Urresti, J., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.07.939256 · Cited by 3 · see citing works

Neurometabolic profiles of autism spectrum disorder patients with genetic variants in specific neurotransmission and synaptic genes

Vilela, J. E. R., Pereira, A. C., Violante, I. R., Mouga, S., Rasga, C., Santos, J. X., Martiniano, H., Marques, A. R., Oliveira, G., Castelo-Branco, M. S., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-20090-x · Cited by 3 · see citing works

SynDB: a Synapse protein DataBase based on synapse ontology

Zhang, W., Zhang, Y., Zheng, H., Zhang, C., Xiong, W., Olyarchuk, J. G., Walker, M., Xu, W., Zhao, M., Zhao, S., et al. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl876 · Cited by 47 · see citing works

G2Cdb: the Genes to Cognition database

Croning, M. D. R., Marshall, M. C., McLaren, P., Armstrong, J. D., & Grant, S. G. N. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn700 · Cited by 75 · see citing works

SynaptopathyDB: a resource for studying the genetic and synaptic basis of nervous system disordersPreprint

Sorokina, O., Dominic, D., Bayés, À., Armstrong, J. D., & Grant, S. G. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.27.661932 · Cited by 4 · see citing works

Synaptome.db: a bioconductor package for synaptic proteomics data

Sorokina, O., Sorokin, A., & Armstrong, J. D. (2022) · Bioinformatics Advances · doi:10.1093/bioadv/vbac086 · Cited by 6 · see citing works

SynaptopathyDB integrates synaptic proteomes, genetic and phenotypic data to advance research on nervous system disorders

Sorokina, O., Dominic, D., Bayés, À., Armstrong, J. D., & Grant, S. G. N. (2025) · Scientific Reports · doi:10.1038/s41598-025-26969-z · Cited by 2 · see citing works