KEGG: Kyoto Encyclopedia of Genes and Genomes

Fast and sensitive protein alignment using DIAMOND

Buchfink, B., Xie, C., & Huson, D. H. (2015) · Nature Methods · doi:10.1038/nmeth.3176 · Cited by 14,201 · see citing works

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799 · see citing works

Diet rapidly and reproducibly alters the human gut microbiome

David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., et al. (2014) · Nature · doi:10.1038/nature12820 · Cited by 10,100 · see citing works

DAVID: Database for Annotation, Visualization, and Integrated Discovery

Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327 · see citing works

Toward understanding the origin and evolution of cellular organisms

Kanehisa, M. (2019) · Protein Science · doi:10.1002/pro.3715 · Cited by 5,509 · see citing works

Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients

Gopalakrishnan, V., Spencer, C. N., Nezi, L., Reuben, A., Andrews, M. C., Karpinets, T. V., Prieto, P. A., Vicente, D., Hoffman, K., Wei, S. C., et al. (2018) · Science · doi:10.1126/science.aan4236 · Cited by 4,812 · see citing works

Functional cartography of complex metabolic networks

Guimerà, R., & Nunes Amaral, L. A. (2005) · Nature · doi:10.1038/nature03288 · Cited by 3,983 · see citing works

A comprehensive two-hybrid analysis to explore the yeast protein interactome

Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., & Sakaki, Y. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.061034498 · Cited by 3,566 · see citing works

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Sanchez-Vega, F., Mina, M., Armenia, J., Chatila, W. K., Luna, A., La, K. C., Dimitriadoy, S., Liu, D. L., Kantheti, H. S., Saghafinia, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.035 · Cited by 3,201 · see citing works

Metabolomics—the link between genotypes and phenotypes

Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445 · see citing works

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0358-2 · Cited by 2,946 · see citing works

Personalized nutrition by prediction of glycemic responses

Zeevi, D., Korem, T., Zmora, N., Israeli, D., Rothschild, D., Weinberger, A., Ben-Yacov, O., Lador, D., Avnit-Sagi, T., Lotan-Pompan, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.001 · Cited by 2,929 · see citing works

Metabolomics: beyond biomarkers and towards mechanisms

Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.25 · Cited by 2,829 · see citing works

MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens

Li, W., Xu, H., Xiao, T., Cong, L., Love, M. I., Zhang, F., Irizarry, R. A., Liu, J. S., Brown, M., & Liu, X. S. (2014) · Genome Biology · doi:10.1186/s13059-014-0554-4 · Cited by 2,684 · see citing works

Integration of biological networks and gene expression data using Cytoscape

Cline, M. S., Smoot, M., Cerami, E., Kuchinsky, A., Landys, N., Workman, C., Christmas, R., Avila-Campilo, I., Creech, M., Gross, B., et al. (2007) · Nature Protocols · doi:10.1038/nprot.2007.324 · Cited by 2,507 · see citing works

Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3

Beghini, F., McIver, L. J., Blanco-Míguez, A., Dubois, L., Asnicar, F., Maharjan, S., Mailyan, A., Manghi, P., Scholz, M., Thomas, A. M., et al. (2021) · eLife · doi:10.7554/elife.65088 · Cited by 2,303 · see citing works

Centering, scaling, and transformations: improving the biological information content of metabolomics data

van den Berg, R. A., Hoefsloot, H. C., Westerhuis, J. A., Smilde, A. K., & van der Werf, M. J. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-142 · Cited by 2,450 · see citing works

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

Villani, A.-C., Satija, R., Reynolds, G., Sarkizova, S., Shekhar, K., Fletcher, J., Griesbeck, M., Butler, A., Zheng, S., Lazo, S., et al. (2017) · Science · doi:10.1126/science.aah4573 · Cited by 2,413 · see citing works

An integrated catalog of reference genes in the human gut microbiome

MetaHIT Consortium, Li, J., Jia, H., Cai, X., Zhong, H., Feng, Q., Sunagawa, S., Arumugam, M., Kultima, J. R., Prifti, E., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2942 · Cited by 2,164 · see citing works

Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis

Scher, J. U., Sczesnak, A., Longman, R. S., Segata, N., Ubeda, C., Bielski, C., Rostron, T., Cerundolo, V., Pamer, E. G., Abramson, S. B., et al. (2013) · eLife · doi:10.7554/elife.01202 · Cited by 2,047 · see citing works

KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold

Aramaki, T., Blanc-Mathieu, R., Endo, H., Ohkubo, K., Kanehisa, M., Goto, S., & Ogata, H. (2019) · doi:10.1101/602110 · Cited by 2,054 · see citing works

Diet Drives Convergence in Gut Microbiome Functions Across Mammalian Phylogeny and Within Humans

Muegge, B. D., Kuczynski, J., Knights, D., Clemente, J. C., González, A., Fontana, L., Henrissat, B., Knight, R., & Gordon, J. I. (2011) · Science · doi:10.1126/science.1198719 · Cited by 1,988 · see citing works

Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

Meyers, R. M., Bryan, J. G., McFarland, J. M., Weir, B. A., Sizemore, A. E., Xu, H., Dharia, N. V., Montgomery, P. G., Cowley, G. S., Pantel, S., et al. (2017) · Nature Genetics · doi:10.1038/ng.3984 · Cited by 1,952 · see citing works

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835 · see citing works

MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data

Huson, D. H., Beier, S., Flade, I., Górska, A., El-Hadidi, M., Mitra, S., Ruscheweyh, H.-J., & Tappu, R. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004957 · Cited by 1,761 · see citing works

Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine

Geller, L. T., Barzily-Rokni, M., Danino, T., Jonas, O. H., Shental, N., Nejman, D., Gavert, N., Zwang, Y., Cooper, Z. A., Shee, K., et al. (2017) · Science · doi:10.1126/science.aah5043 · Cited by 1,817 · see citing works

Personalized Gut Mucosal Colonization Resistance to Empiric Probiotics Is Associated with Unique Host and Microbiome Features

Zmora, N., Zilberman-Schapira, G., Suez, J., Mor, U., Dori-Bachash, M., Bashiardes, S., Kotler, E., Zur, M., Regev-Lehavi, D., Brik, R. B.-Z., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.041 · Cited by 1,695 · see citing works

Exploring tissue architecture using spatial transcriptomics

Rao, A., Barkley, D., França, G. S., & Yanai, I. (2021) · Nature · doi:10.1038/s41586-021-03634-9 · Cited by 1,700 · see citing works

A N <scp>EW</scp> A <scp>PPROACH TO</scp> D <scp>ECODING</scp> L <scp>IFE</scp> : Systems Biology

Ideker, T., Galitski, T., & Hood, L. (2001) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.2.1.343 · Cited by 1,664 · see citing works

Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug

Wu, H., Esteve, E., Tremaroli, V., Khan, M. T., Caesar, R., Mannerås-Holm, L., Ståhlman, M., Olsson, L. M., Serino, M., Planas-Fèlix, M., et al. (2017) · Nature Medicine · doi:10.1038/nm.4345 · Cited by 1,632 · see citing works

CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning

Chklovski, A., Parks, D. H., Woodcroft, B. J., & Tyson, G. W. (2023) · Nature Methods · doi:10.1038/s41592-023-01940-w · Cited by 1,705 · see citing works

Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes

Riquelme, E., Zhang, Y., Zhang, L., Montiel, M., Zoltan, M., Dong, W., Quesada, P., Sahin, I., Chandra, V., San Lucas, A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.008 · Cited by 1,577 · see citing works

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

Fritsche, L. G., Igl, W., Bailey, J. N. C., Grassmann, F., Sengupta, S., Bragg-Gresham, J. L., Burdon, K. P., Hebbring, S. J., Wen, C., Gorski, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3448 · Cited by 1,544 · see citing works

New genetic loci link adipose and insulin biology to body fat distribution

The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature · doi:10.1038/nature14132 · Cited by 1,580 · see citing works

Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention

Liu, R., Hong, J., Xu, X., Feng, Q., Zhang, D., Gu, Y., Shi, J., Zhao, S., Liu, W., Wang, X., et al. (2017) · Nature Medicine · doi:10.1038/nm.4358 · Cited by 1,501 · see citing works

Transkingdom Control of Microbiota Diurnal Oscillations Promotes Metabolic Homeostasis

Thaiss, C. A., Zeevi, D., Levy, M., Zilberman-Schapira, G., Suez, J., Tengeler, A. C., Abramson, L., Katz, M. N., Korem, T., Zmora, N., et al. (2014) · Cell · doi:10.1016/j.cell.2014.09.048 · Cited by 1,449 · see citing works

Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer

Yachida, S., Mizutani, S., Shiroma, H., Shiba, S., Nakajima, T., Sakamoto, T., Watanabe, H., Masuda, K., Nishimoto, Y., Kubo, M., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0458-7 · Cited by 1,429 · see citing works

Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing

Cusanovich, D. A., Daza, R., Adey, A., Pliner, H. A., Christiansen, L., Gunderson, K. L., Steemers, F. J., Trapnell, C., & Shendure, J. (2015) · Science · doi:10.1126/science.aab1601 · Cited by 1,248 · see citing works

Colonic bacterial composition in Parkinson's disease

Keshavarzian, A., Green, S. J., Engen, P. A., Voigt, R. M., Naqib, A., Forsyth, C. B., Mutlu, E., & Shannon, K. M. (2015) · Movement Disorders · doi:10.1002/mds.26307 · Cited by 1,281 · see citing works

Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health

Oliphant, K., & Allen-Vercoe, E. (2019) · Microbiome · doi:10.1186/s40168-019-0704-8 · Cited by 1,327 · see citing works

Personal omics profiling reveals dynamic molecular and medical phenotypes

Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y. K., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.009 · Cited by 1,291 · see citing works

Next-Generation Sequencing Technology: Current Trends and Advancements

Satam, H., Joshi, K., Mangrolia, U., Waghoo, S., Zaidi, G., Rawool, S., Thakare, R. P., Banday, S., Mishra, A. K., Das, G., et al. (2023) · Biology · doi:10.3390/biology12070997 · Cited by 1,299 · see citing works

Enterotypes in the landscape of gut microbial community composition

Costea, P. I., Hildebrand, F., Arumugam, M., Bäckhed, F., Blaser, M. J., Bushman, F. D., de Vos, W. M., Ehrlich, S. D., Fraser, C. M., Hattori, M., et al. (2017) · Nature Microbiology · doi:10.1038/s41564-017-0072-8 · Cited by 1,138 · see citing works

Deciphering cell–cell interactions and communication from gene expression

Armingol, E., Officer, A., Harismendy, O., & Lewis, N. E. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00292-x · Cited by 1,267 · see citing works

Biogeography and individuality shape function in the human skin metagenome

Program, N. C. S., Oh, J., Byrd, A. L., Deming, C., Conlan, S., Kong, H. H., & Segre, J. A. (2014) · Nature · doi:10.1038/nature13786 · Cited by 1,148 · see citing works

GABA-modulating bacteria of the human gut microbiota

Strandwitz, P., Kim, K. H., Terekhova, D., Liu, J. K., Sharma, A., Levering, J., McDonald, D., Dietrich, D., Ramadhar, T. R., Lekbua, A., et al. (2018) · Nature Microbiology · doi:10.1038/s41564-018-0307-3 · Cited by 1,170 · see citing works

Post-Antibiotic Gut Mucosal Microbiome Reconstitution Is Impaired by Probiotics and Improved by Autologous FMT

Suez, J., Zmora, N., Zilberman-Schapira, G., Mor, U., Dori-Bachash, M., Bashiardes, S., Zur, M., Regev-Lehavi, D., Ben-Zeev Brik, R., Federici, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.08.047 · Cited by 1,184 · see citing works

Role of Catalase in Oxidative Stress- and Age-Associated Degenerative Diseases

Nandi, A., Yan, L.-J., Jana, C. K., & Das, N. (2019) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2019/9613090 · Cited by 1,185 · see citing works

Metal ions in biological catalysis: from enzyme databases to general principles

Andreini, C., Bertini, I., Cavallaro, G., Holliday, G. L., & Thornton, J. M. (2008) · JBIC Journal of Biological Inorganic Chemistry · doi:10.1007/s00775-008-0404-5 · Cited by 1,150 · see citing works

Methods of integrating data to uncover genotype-phenotype interactions

Ritchie, M. D., Holzinger, E. R., Li, R., Pendergrass, S. A., & Kim, D. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3868 · Cited by 1,085 · see citing works

High-throughput generation, optimization and analysis of genome-scale metabolic models

Henry, C. S., DeJongh, M., Best, A. A., Frybarger, P. M., Linsay, B., & Stevens, R. L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1672 · Cited by 1,090 · see citing works

The Short Chain Fatty Acid Butyrate Imprints an Antimicrobial Program in Macrophages

Schulthess, J., Pandey, S., Capitani, M., Rue-Albrecht, K. C., Arnold, I., Franchini, F., Chomka, A., Ilott, N. E., Johnston, D. G. W., Pires, E., et al. (2019) · Immunity · doi:10.1016/j.immuni.2018.12.018 · Cited by 1,037 · see citing works

The physiology and habitat of the last universal common ancestor

Weiss, M. C., Sousa, F. L., Mrnjavac, N., Neukirchen, S., Roettger, M., Nelson-Sathi, S., & Martin, W. F. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.116 · Cited by 1,049 · see citing works

Feedback between p21 and reactive oxygen production is necessary for cell senescence

Passos, J. F., Nelson, G., Wang, C., Richter, T., Simillion, C., Proctor, C. J., Miwa, S., Olijslagers, S., Hallinan, J., Wipat, A., et al. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.5 · Cited by 1,019 · see citing works

A novel signaling pathway impact analysis

Tarca, A. L., Draghici, S., Khatri, P., Hassan, S. S., Mittal, P., Kim, J.-S., Kim, C. J., Kusanovic, J. P., & Romero, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btn577 · Cited by 1,031 · see citing works

Is My Network Module Preserved and Reproducible?

Langfelder, P., Luo, R., Oldham, M. C., & Horvath, S. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001057 · Cited by 1,012 · see citing works

SIRT5-mediated lysine desuccinylation impacts diverse metabolic pathways

Park, J., Chen, Y., Tishkoff, D. X., Peng, C., Tan, M., Dai, L., Xie, Z., Zhang, Y., Zwaans, B. M. M., Skinner, M. E., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.06.001 · Cited by 1,000 · see citing works

Microbiota-modulated metabolites shape the intestinal microenvironment by regulating NLRP6 inflammasome signaling

Levy, M., Thaiss, C. A., Zeevi, D., Dohnalová, L., Zilberman-Schapira, G., Mahdi, J. A., David, E., Savidor, A., Korem, T., Herzig, Y., et al. (2015) · Cell · doi:10.1016/j.cell.2015.10.048 · Cited by 960 · see citing works

The yak genome and adaptation to life at high altitude

Qiu, Q., Zhang, G., Ma, T., Qian, W., Wang, J., Ye, Z., Cao, C., Hu, Q., Kim, J., Larkin, D. M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2343 · Cited by 971 · see citing works

A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain

Davie, K., Janssens, J., Koldere, D., De Waegeneer, M., Pech, U., Kreft, Ł., Aibar, S., Makhzami, S., Christiaens, V., Bravo González-Blas, C., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.057 · Cited by 840 · see citing works

Microbiota Diurnal Rhythmicity Programs Host Transcriptome Oscillations

Thaiss, C. A., Levy, M., Korem, T., Dohnalová, L., Shapiro, H., Jaitin, D. A., David, E., Winter, D. R., Gury-BenAri, M., Tatirovsky, E., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.003 · Cited by 870 · see citing works

Using machine learning approaches for multi-omics data analysis: A review

Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903 · see citing works

Individual intestinal symbionts induce a distinct population of RORγ ⁺ regulatory T cells

Sefik, E., Geva-Zatorsky, N., Oh, S., Konnikova, L., Zemmour, D., McGuire, A. M., Burzyn, D., Ortiz-Lopez, A., Lobera, M., Yang, J., et al. (2015) · Science · doi:10.1126/science.aaa9420 · Cited by 879 · see citing works

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

Gillette, M. A., Satpathy, S., Cao, S., Dhanasekaran, S. M., Vasaikar, S. V., Krug, K., Petralia, F., Li, Y., Liang, W.-W., Reva, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.013 · Cited by 820 · see citing works

Single-Cell RNA-Seq with Waterfall Reveals Molecular Cascades underlying Adult Neurogenesis

Shin, J., Berg, D. A., Zhu, Y., Shin, J. Y., Song, J., Bonaguidi, M. A., Enikolopov, G., Nauen, D. W., Christian, K. M., Ming, G.-L., et al. (2015) · Cell Stem Cell · doi:10.1016/j.stem.2015.07.013 · Cited by 784 · see citing works

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

Clark, D. J., Dhanasekaran, S. M., Petralia, F., Pan, J., Song, X., Hu, Y., da Veiga Leprevost, F., Reva, B., Lih, T.-S. M., Chang, H.-Y., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.007 · Cited by 730 · see citing works

Daily sampling reveals personalized diet-microbiome associations in humans

Johnson, A. J., Vangay, P., Al-Ghalith, G. A., Hillmann, B. M., Ward, T. L., Shields-Cutler, R. R., Kim, A. D., Shmagel, A. K., Syed, A. N., Walter, J., et al. (2019) · Cell Host &amp; Microbe · doi:10.1016/j.chom.2019.05.005 · Cited by 742 · see citing works

HER kinase inhibition in patients with HER2- and HER3-mutant cancers

Hyman, D. M., Piha-Paul, S. A., Won, H., Rodon, J., Saura, C., Shapiro, G. I., Juric, D., Quinn, D. I., Moreno, V., Doger, B., et al. (2018) · Nature · doi:10.1038/nature25475 · Cited by 780 · see citing works

A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

Zhong, S., Zhang, S., Fan, X., Wu, Q., Yan, L., Dong, J., Zhang, H., Li, L., Sun, L., Pan, N., et al. (2018) · Nature · doi:10.1038/nature25980 · Cited by 689 · see citing works

Massive mining of publicly available RNA-seq data from human and mouse

Lachmann, A., Torre, D., Keenan, A. B., Jagodnik, K. M., Lee, H. J., Wang, L., Silverstein, M. C., & Ma’ayan, A. (2018) · Nature Communications · doi:10.1038/s41467-018-03751-6 · Cited by 701 · see citing works

The ctenophore genome and the evolutionary origins of neural systems

Moroz, L. L., Kocot, K. M., Citarella, M. R., Dosung, S., Norekian, T. P., Povolotskaya, I. S., Grigorenko, A. P., Dailey, C., Berezikov, E., Buckley, K. M., et al. (2014) · Nature · doi:10.1038/nature13400 · Cited by 716 · see citing works

New insights from uncultivated genomes of the global human gut microbiome

Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S., & Kyrpides, N. C. (2019) · Nature · doi:10.1038/s41586-019-1058-x · Cited by 737 · see citing works

Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses

Gilman, S. R., Iossifov, I., Levy, D., Ronemus, M., Wigler, M., & Vitkup, D. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.021 · Cited by 701 · see citing works

Foxp3 occupancy and regulation of key target genes during T-cell stimulation

Marson, A., Kretschmer, K., Frampton, G. M., Jacobsen, E. S., Polansky, J. K., MacIsaac, K. D., Levine, S. S., Fraenkel, E., von Boehmer, H., & Young, R. A. (2007) · Nature · doi:10.1038/nature05478 · Cited by 724 · see citing works

Cognitive impairment by antibiotic-induced gut dysbiosis: analysis of gut microbiota-brain communication

Fröhlich, E. E., Farzi, A., Mayerhofer, R., Reichmann, F., Jačan, A., Wagner, B., Zinser, E., Bordag, N., Magnes, C., Fröhlich, E., et al. (2016) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2016.02.020 · Cited by 720 · see citing works

Functional genomic hypothesis generation and experimentation by a robot scientist

King, R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S. H., Kell, D. B., & Oliver, S. G. (2004) · Nature · doi:10.1038/nature02236 · Cited by 662 · see citing works

Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome

Shi, Y., Zhao, H., Shi, Y., Cao, Y., Yang, D., Li, Z., Zhang, B., Liang, X., Li, T., Chen, J., et al. (2012) · Nature Genetics · doi:10.1038/ng.2384 · Cited by 678 · see citing works

Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome

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