Gene Ontology Analysis of GWA Study Data Sets Provides Insights into the Biology of Bipolar Disorder

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442

The Gene Ontology (GO) database and informatics resource

Gene Ontology Consortium (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh036 · Cited by 4,596

MANIC DEPRESSIVE ILLNESS

Davenport, Y. B., Adland, M. L., Gold, P. W., & Goodwin, F. K. (1984) · The Lancet · doi:10.1016/s0140-6736(84)92810-1 · Cited by 2,925

The Wellcome Trust Case Control Consortium, U.K.

Mossman, K. (2008) · Scientific American · doi:10.1038/scientificamerican0108-42a · Cited by 2,714

A new multipoint method for genome-wide association studies by imputation of genotypes

Marchini, J., Howie, B., Myers, S., McVean, G., & Donnelly, P. (2007) · Nature Genetics · doi:10.1038/ng2088 · Cited by 2,609

Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease

the NIDDK IBD Genetics Consortium, Barrett, J. C., the Belgian-French IBD Consortium, the Wellcome Trust Case Control Consortium, Hansoul, S., Nicolae, D. L., Cho, J. H., Duerr, R. H., Rioux, J. D., Brant, S. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.175 · Cited by 2,593

Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes

Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science · doi:10.1126/science.1142364 · Cited by 2,194

A Simple Correction for Multiple Testing for Single-Nucleotide Polymorphisms in Linkage Disequilibrium with Each Other

Nyholt, D. R. (2004) · The American Journal of Human Genetics · doi:10.1086/383251 · Cited by 1,699

Walking the Interactome for Prioritization of Candidate Disease Genes

Köhler, S., Bauer, S., Horn, D., & Robinson, P. N. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.02.013 · Cited by 1,268

GenNet framework: interpretable neural networks for phenotype predictionPreprint

van Hilten, A., Kushner, S. A., Kayser, M., Ikram, M. A., Adams, H. H. H., Klaver, C. C. W., Niessen, W. J., & Roshchupkin, G. V. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.19.159152 · Cited by 7

Breaking Free from the Chains of Pathway Annotation: de Novo Pathway Discovery for the Analysis of Disease Processes

Lehne, B. C., & Schlitt, T. (2012) · Pharmacogenomics · doi:10.2217/pgs.12.170 · Cited by 6

Regional enrichment analyses on genetic profiles for schizophrenia and bipolar disorder

Liu, J., Chen, J., Perrone‐Bizzozero, N. I., Turner, J. A., & Calhoun, V. D. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.04.033 · Cited by 6

An Enrichment Analysis for Cardiometabolic Traits Suggests Non-Random Assignment of Genes to microRNAs

Mustafa, R., Ghanbari, M., Evangelou, M., & Dehghan, A. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19113666 · Cited by 6

Pathway analysis for family data using nested random-effects models

Houwing‐Duistermaat, J. J., Uh, H., & Tsonaka, R. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s22 · Cited by 6

Correction: Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Jones, L., Holmans, P., Hamshere, M. L., Harold, D. H., Moskvina, V., Ivanov, D. K., Pocklington, A. J., Abraham, R., Hollingworth, P., Sims, R., et al. (2011) · PLoS ONE · doi:10.1371/annotation/a0bb886d-d345-4a20-a82e-adce9b047798 · Cited by 6

META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies

Rosenberger, A., Friedrichs, S., Amos, C. I., Brennan, P., Fehringer, G., Heinrich, J., Hung, R. J., Muley, T., Müller‐Nurasyid, M., Risch, A., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140179 · Cited by 5

Pathway-Guided Identification of Gene-Gene Interactions

Wang, X., Zhang, D., & Tzeng, J. (2014) · Annals of Human Genetics · doi:10.1111/ahg.12080 · Cited by 5

Incorporating Prior Knowledge to Increase the Power of Genome-Wide Association Studies

Petersen, A., Spratt, J., & Tintle, N. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-447-0_25 · Cited by 4

Study of genetic correlation between children’s sleep and obesity

Mei, H., Jiang, F., Li, L., Griswold, M. E., Liu, S., & Mosley, T. H. (2020) · Journal of Human Genetics · doi:10.1038/s10038-020-0791-1 · Cited by 5

Genetics of Psychiatric Disorders

Nürnberger, J. I., Berrettini, W., & Niculescu, A. B. (2016) · Springer eBooks · doi:10.1007/978-1-4939-2528-5_29 · Cited by 6

Gene-set Enrichment with Mathematical Biology (GEMB)

Cochran, A. L., Nieser, K. J., Forger, D. B., Zöllner, S. K., & McInnis, M. G. (2020) · GigaScience · doi:10.1093/gigascience/giaa091 · Cited by 2

Novel Integrative Genomics Approach for Associating GWAS Information with Intrinsic Subtypes of Breast Cancer

Hicks, C., Koganti, T., Brown, A. S., Monico, J., Backus, K. V., & Miele, L. (2013) · Cancer Informatics · doi:10.4137/cin.s11452 · Cited by 4

Research Highlights: Highlights from the Latest Articles Focusing on a New Gene Set for Better Drug Response Prediction of Epilepsy Patients

Baghel, R., Jajodia, A., Grover, S., & Kukreti, R. (2014) · Pharmacogenomics · doi:10.2217/pgs.14.11 · Cited by 4

PoCos: Population Covering Locus Sets for Risk Assessment in Complex Diseases

Ayati, M., & Koyutürk, M. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005195 · Cited by 4

Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from matched micro-RNA and gene expression data

Patrick, E., Buckley, M. J., Müller, S., Lin, D. M., & Yang, J. Y. H. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv220 · Cited by 5

Emerging trends in gene and bipolar disorder research: a bibliometric analysis and network visualisation

Zakaria, W. N. A., Wijaya, A., Al-Rahbi, B., Ahmad, A. H., Zakaria, R., & Othman, Z. (2023) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000338 · Cited by 4

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Hasib, R. A., Ali, M. C., Rahman, M. H., Ahmed, S., Sultana, S., Summa, S. Z., Shimu, M. S. S., Afrin, Z., & Jamal, M. A. H. M. (2023) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2023.2262586 · Cited by 3

Assessing the collective disease association of multiple genomic loci

Ayati, M., & Koyutürk, M. (2015) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2808719.2808758 · Cited by 3

Pathway-Wide Genetic Risks in Chlamydial Infections Overlap between Tissue Tropisms: A Genome-Wide Association Scan

Roberts, C. H., Ouburg, S., Preston, M. D., de Vries, H. J. C., Holland, M. J., & Morré, S. A. (2018) · Mediators of Inflammation · doi:10.1155/2018/3434101 · Cited by 3

Pathway-based analysis for genome-wide association studies of schizophrenia to provide new insight in schizophrenia study

Zhang, K., Zhang, L., Zhang, W., & Wang, J. (2011) · Chinese Science Bulletin · doi:10.1007/s11434-011-4742-2 · Cited by 3

Whole-Genome Pathway Analysis on 132,497 Individuals Identifies Novel Gene-Sets Associated with Body Mass Index

Simonson, M. A., McQueen, M. B., & Keller, M. C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0078546 · Cited by 3

Potpourri: An Epistasis Test Prioritization Algorithm via Diverse SNP Selection

Çaylak, G., Taştan, Ö., & Çiçek, A. E. (2020) · Journal of Computational Biology · doi:10.1089/cmb.2020.0429 · Cited by 2

Gene Ontology and Pathway Enrichment Analysis

Gupta, M. K., Gouda, G., Sabarinathan, S., Donde, R., Dash, G. K., Vadde, R., & Behera, L. (2021) · Springer eBooks · doi:10.1007/978-981-16-3993-7_12 · Cited by 3

Transcriptome Study in Sicilian Patients with Autism Spectrum Disorder

Salemi, M., Schillaci, F. A., Lanza, G., Marchese, G., Salluzzo, M. G., Cordella, A., Caniglia, S., Bruccheri, M. G., Truda, A., Greco, D., et al. (2024) · Biomedicines · doi:10.3390/biomedicines12071402 · Cited by 3

Genomics software: The view from 10,000 feet

Weale, M. E. (2009) · Human Genomics · doi:10.1186/1479-7364-4-1-56 · Cited by 2

Novel Somatic Copy Number Alteration Identified for Cervical Cancer in the Mexican American Population

Torabi, A., Ordoñez, J., Su, B., Palmer, L., Mao, C., Lara, K. K., Rubin, L. P., & Xu, C. D. (2016) · Medical Sciences · doi:10.3390/medsci4030012 · Cited by 2

Bipolar Disorder

Fears, S. C., & Reus, V. I. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-410529-4.00104-2 · Cited by 2

The Trilogy of GxE : Conceptualization, Operationalization, and Application

Grigorenko, E. L., Bick, J. R., Campbell, D. J., Lewine, G., Abrams, J., Nguyen, V. T., & Chang, J. T. (2016) · Wiley eBooks · doi:10.1002/9781119125556.devpsy208 · Cited by 2

Potpourri: An Epistasis Test Prioritization Algorithm via Diverse SNP SelectionPreprint

Çaylak, G., Taştan, Ö., & Çiçek, A. E. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/830216 · Cited by 2

Genomic regions associated with pseudorabies virus infection status in naturally infected feral swine (Sus scrofa)

Bowden, C. F., Kiser, J. N., Miller, R. S., Buckley, A., Boggiatto, P. M., Giglio, R. M., Brown, V. R., Garrick, D. J., Neibergs, H. L., Piaggio, A. J., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1292671 · Cited by 2

for Genome-wide Association Studies

Liu, J. Z., McRae, A. F., Nyholt, D. R., Medland, S. E., Wray, N. R., Brown, K. M., Amfs Investigators, Hayward, N. K., Montgomery, G. W., Visscher, P. M., et al. (2010) · Cited by 1

Applying In Silico Integrative Genomics to Genetic Studies of Human Disease

Saccone, S. F. (2012) · International review of neurobiology · doi:10.1016/b978-0-12-388408-4.00007-1 · Cited by 1

Interpreting Association Signals

Soranzo, N., & Dudbridge, F. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-375142-3.10016-1 · Cited by 1

A Bayesian Hierarchical Framework for Pathway Analysis in Genome-Wide Association Studies

Zhang, L., Papachristou, C., Choudhary, P. K., & Biswas, S. (2019) · Human Heredity · doi:10.1159/000508664 · Cited by 1

A Network-Based Approach for Improving Annotation of Transcription Factor Functions and Binding Sites in Arabidopsis thaliana

Najnin, T., Saimon, S. H., Sunter, G., & Ruan, J. (2023) · Genes · doi:10.3390/genes14020282 · Cited by 1

From Linkage to GWAS: A Multifaceted Exploration of the Genetic Risk for Alcohol Dependence

Adkins, A. E. (2012) · VCU Scholars Compass (Virginia Commonwealth University) · doi:10.25772/cpqn-8g96 · Cited by 1

Multilevel-analysis identify a cis-expression quantitative trait locus associated with risk of renal cell carcinoma

Shu, X., Purdue, M. P., Ye, Y., Wood, C. G., Chen, M., Wang, Z., Albanes, D., Pu, X., Huang, M., Stevens, V. L., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.3001 · Cited by 1

An assessment of the catecholamine hypothesis of bipolar disorder

Charney, A. W., Sayed, S., & Charney, D. S. (2016) · Cambridge University Press eBooks · doi:10.1017/cbo9781107477278.004 · Cited by 1

Genetic Contribution of Variants in GABAergic Signaling to Nicotine Dependence

Li, M. D. (2018) · Springer eBooks · doi:10.1007/978-981-10-7530-8_7 · Cited by 1

Genetic studies of the common epilepsies: genome-wide association studies in the partial epilepsies

Catarino, C. B. (2014) · UCL Discovery (University College London) · Cited by 1

Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of diseasePreprint

Carbonetto, P. S., & Stephens, M. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1208.4400 · Cited by 1

Novel bioinformatics approach to investigate quantitative phenotype-genotype associations in neuroimaging studiesPreprint

Patel, S., Park, M. T. M., Chakravarty, M. M., & Knight, J. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/015065 · Cited by 1

Significant enrichment of Herpesvirus interactors in GWAS data suggests causal inferences for the association between Epstein Barr virus and multiple sclerosisPreprint

Mechelli, R., Umeton, R., Srinivasan, S., Fornasiero, A., Ferraldeschi, M., WTCCC2, I. A., Centonze, D., Farina, C., Salvetti, M., & Ristori, G. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/624049 · Cited by 1

Enrichment of genomic variation in pathways linked to autismPreprint

Esteban, F. J., Tonellato, P. J., & Wall, D. P. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.19.346072 · Cited by 1

Large Scale Machine Learning in Biology

Raj, A. (2011) · doi:10.7916/d82n5863

Computational Contributions Towards Scalable and Efficient Genome-wide Association Methodology

Prabhu, S. (2013) · doi:10.7916/d8r78nf0

Gene and Gene-Set Analysis for Genome-Wide Association StudiesPreprint

Pedroso, I. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1308.4102

Identifying Highly Conserved and Highly Differentiated Gene Ontology Categories in Human Populations

Jiang, Y., Zhang, R., Sun, P. G., Tang, G., Zhang, X., Wang, X., Guo, X., Wang, Q., & Li, X. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027871

Genetic mechanisms underlying autism spectrum disorders

Kilpinen, H. (2010) · Työväentutkimus Vuosikirja

Ultra-Deep Sequencing of Bisulfite-Modified DNA

Qin, T., Park, Y., Figueroa, M. E., & Sartor, M. A. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-800140-0.00003-0

Behavior Genetics Association 41st Annual Meeting Abstracts

Nolte, I., de Geus, E. J. C., Whitsel, E., Kerr, K., van Beijsterveldt, C. E. M., Oldehinkel, A., Ehli, E. A., Davies, G., Dierckx, B., Lefrandt, J., et al. (2011) · Behavior Genetics · doi:10.1007/s10519-011-9495-9

Pathways to dementia: genetic predictors of cognitive and brain imaging endophenotypes in Alzheimer's disease

Ramanan, V. K. (2014) · IUScholarWorks (Indiana University) · doi:10.7912/c2/1951

Correction: Pathway Analysis of Smoking Quantity in Multiple GWAS Identifies Cholinergic and Sensory Pathways

Harari, O., Wang, J., Bucholz, K. K., Edenberg, H. J., Heath, A. C., Martin, N. G., Pergadia, M. L., Montgomery, G. W., Schrage, A. J., Bierut, L. J., et al. (2013) · PLoS ONE · doi:10.1371/annotation/21033005-e120-4364-8024-c6534b4108f6

Schizophrenia and Bipolar Disorder

Williams, H. J., O’Donovan, M. C., Craddock, N. J., & Owen, M. J. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-382227-7.00088-4

Gene-Set Meta-Analysis to Discover Molecular-Biological Pathways Associated to Lung Cancer

Rosenberger, A. (2017) · doi:10.53846/goediss-6339

Genetic Interactions and Complex Human Diseases

Wang, W. (2017) · University of Minnesota Digital Conservancy (University of Minnesota)

PRaDA : Web-based analyzer for Pathway Relation and Disease Associated SNP

Yu, K., Park, S. H., & Ryu, K. H. (2018) · Journal of Digital Contents Society · doi:10.9728/dcs.2018.19.9.1795

Genetic Association from RFLPs to Millions of Variant Markers: Unravelling the Genetic Complexity of Diseases

Banaganapalli, B., Shaik, N. A., Al-Aama, J. Y., & Elango, R. (2019) · Springer eBooks · doi:10.1007/978-3-030-18375-2_2

Pathways with Genomic Variation in Family DNA Microarrays Linked to Autism Risk InheritancePreprint

Wall, D. P., Esteban, F. J., & Tonellato, P. J. (2020) · Preprints.org · doi:10.20944/preprints202011.0311.v1

Enrichment analysis of GWAS data in autoimmunity delineates the multiple sclerosis-Epstein Barr virus associationPreprint

Mechelli, R., Umeton, R., Rinaldi, V., Bellucci, G., Bigi, R., Angelini, D. F., Guerrera, G., Srinivasan, S., Romano, S., Buscarinu, M. C., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.06.447253

Statistical approaches of gene set analysis with quantitative trait loci for high-throughput genomic studies.

Das, S. (2020) · ThinkIR: The University of Louisville's Institutional Repository (University of Louisville) · doi:10.18297/etd/3537

Linkage and Association Studies of Substance Use Disorders

Maher, B. S. (2022) · Springer eBooks · doi:10.1007/978-3-030-95350-8_7

Drug Discovery in Psychiatry: Time for Human Genome-Guided Solutions

Papassotiropoulos, A., & de Quervain, D. J. ‐. (2019) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-803161-2.00014-x

Peer Review #1 of "Evaluating the adaptive evolutionary convergence of carnivorous plant taxa through functional genomics (v0.2)"

(2018) · PeerJ · doi:10.7287/peerj.4322v0.2/reviews/1

Peer Review #2 of "Evaluating the adaptive evolutionary convergence of carnivorous plant taxa through functional genomics (v0.2)"

(2018) · PeerJ · doi:10.7287/peerj.4322v0.2/reviews/2

Peer Review #2 of "Evaluating the adaptive evolutionary convergence of carnivorous plant taxa through functional genomics (v0.1)"

(2018) · PeerJ · doi:10.7287/peerj.4322v0.1/reviews/2

Faculty Opinions recommendation of Synthesizing genome-wide association studies and expression microarray reveals novel genes that act in the human growth plate to modulate height.

Meulenbelt, I., & Ramos, Y. F. (2012) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.717957216.793461724

Peer Review #1 of "Evaluating the adaptive evolutionary convergence of carnivorous plant taxa through functional genomics (v0.1)"

(2018) · PeerJ · doi:10.7287/peerj.4322v0.1/reviews/1

Faculty Opinions recommendation of Glucocorticoid therapy regulates podocyte motility by inhibition of Rac1.

Saleem, M. A. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.727847829.793566370

A statistical perspective of gene set analysis with trait-specific QTL in molecular crop breeding

Das, S., & Rai, S. N. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-85243-2.00005-2

Hierarchical association of COPD to principal genetic components of biological systems

Carlin, D. E., Larsen, S. J., Sirupurapu, V., Cho, M. H., Silverman, E. K., Baumbach, J., & Ideker, T. (2023) · PLoS ONE · doi:10.1371/journal.pone.0286064

Using the Bayesian variational spike and slab model in a genome‐wide association study for finding associated loci with bipolar disorder

Naeini, M. K., Akbarzadeh, M., Kazemi, I., Speed, D., & Hosseini, S. M. (2023) · Annals of Human Genetics · doi:10.1111/ahg.12538

Approaches to Studying Human Genetics

Veatch, O. J. (2024) · Springer eBooks · doi:10.1007/978-3-031-62723-1_8

Additional file 1 of Exome localization of complex disease association signals

Lehne, B., Lewis, C. M., & Schlitt, T. (2020) · Figshare · doi:10.6084/m9.figshare.12880463

Additional file 2 of Exome localization of complex disease association signals

Lehne, B., Lewis, C. M., & Schlitt, T. (2020) · Figshare · doi:10.6084/m9.figshare.12880466

Interactions gène-gène et gène-environnement dans les études génétiques de maladies multifactorielles : application à l’asthme et l’atopie

Sugier, P. (2018) · theses.fr (ABES) · doi:10.70675/123d2373z6e08z4413z97bez1dd3c88e63a0

Variable selection for data aggregated from different sources with group of variable structure

Broc, C. (2019) · theses.fr (ABES) · doi:10.70675/3dc1a424z73f4z46e3z96efze45d770ca70e

Pathway-based analysis for genome-wide association study data of bipolar disorder provides new insights for genetic study

Suhua, Chang, Jinglu, Wang, Kunlin, Zhang, & Jing (2015) · 蛋白质与细胞：英文版

Pathway Analysis Using Information from Allele-Specific Gene Methylation in Genome-Wide Association Studies for Bipolar Disorder

Chuang, L.-C., Kao, C.-F., Shih, W., & Kuo, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0053092 · Cited by 28

Identification of Pathways for Bipolar Disorder: A Meta-analysis

Nurnberger, J. I., Koller, D. L., Jung, J., Edenberg, H. J., Foroud, T., Guella, I., Vawter, M. P., & Kelsoe, J. R. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.176 · Cited by 234

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder. PLoS ONE

Chuang, L.-C., Kao, C.-F., Shih, W.-L., & Kuo, P.-H. (2012)

Identification of Pathways for Bipolar Disorder AMeta-analysis

Nürnberger, J. I., Daniel, P., Koller, L., Jung, J., Howard, P., Edenberg, H. J., Foroud, T., Guella, I., Marquis, P., Vawter, P., et al. (2016)