The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Topology of viral evolution
Open accessAbstract
Significance: Evolution is mediated not only by random mutations over a number of generations (vertical evolution), but also through the mixture of genomic material between individuals of different lineages (horizontal evolution). The standard evolutionary representation, the phylogenetic tree, faithfully represents the former but not the latter scenario. Although many elaborations have been developed to address this issue, there is still no agreed-upon method of incorporating both vertical and horizontal evolution. Here, we present an alternative strategy based on algebraic topology to study evolution. This method extends beyond the limits of a tree to capture directly even complex horizontal exchanges between multiple parental strains, as well as uncover broader reticulate patterns, including the segregation of segments during reassortment.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In the case of strict clonal evolution, all information is captured by the zero-dimensional homology.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“However, the metric space produced by using the concatenated sequences did produce significant onedimensional homology, which would preclude phylogeny as a complete explanation.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“When each distinct segment was studied, there was no higher-dimensional behaviour.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“By performing persistent homological calculations on simulations, it was observed that a lower bound for the recombination/reassortment rate was obtained by studying the counts of the number of bars in the corresponding barcode.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“The type of exchange of genomic material can be catalogued by the topology of the genomic data.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“Persistent homology shows higher-dimensional homology groups capturing some of the complex recombinant structures.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“when analysing the homology of avian influenza A, it was shown that several segments, containing the genes that encode the polymerases, are more likely to co-segregate together”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
In the citing paper
“In the cases studied, these occurrences were consistent with the known horizontal transfer mechanisms in these situations.”
From Topological pattern recognition for point cloud data (2014) · cites this paper as Chan et al. (2013)
Citations
Cites
Application of Phylogenetic Networks in Evolutionary Studies
Huson, D. H., & Bryant, D. (2005) · Molecular Biology and Evolution · doi:10.1093/molbev/msj030 · Cited by 8,895
Wooding, S. (2004) · The American Journal of Human Genetics · doi:10.1086/383584 · Cited by 3,093
Human Infection with a Novel Avian-Origin Influenza A (H7N9) Virus
Gao, R., Cao, B., Hu, Y., Feng, Z., Wang, D., Hu, W., Chen, J., Jie, Z., Qiu, H., Xu, K., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1304459 · Cited by 2,310
Phylogenetic Classification and the Universal Tree
Doolittle, W. F. (1999) · Science · doi:10.1126/science.284.5423.2124 · Cited by 1,888
Smith, J. M., Smith, N. H., O'Rourke, M., & Spratt, B. G. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.10.4384 · Cited by 1,802
Analyzing the mosaic structure of genes
Smith, J. (1992) · Journal of Molecular Evolution · doi:10.1007/bf00182389 · Cited by 1,630
Zomorodian, A., & Carlsson, G. (2005) · Discrete & Computational Geometry · doi:10.1007/s00454-004-1146-y · Cited by 1,591
Self-citationFouchier, R. A. M., Munster, V. J., Wallensten, A., Bestebroer, T. M., Herfst, S., Smith, D. J., Rimmelzwaan, G. F., Olsén, B., & Osterhaus, A. D. M. E. (2005) · Journal of Virology · doi:10.1128/jvi.79.5.2814-2822.2005 · Cited by 1,565
A Simple and Robust Statistical Test for Detecting the Presence of Recombination
Bruen, T. C., Philippe, H., & Bryant, D. (2006) · Genetics · doi:10.1534/genetics.105.048975 · Cited by 1,366
Drummond, A. J., Nicholls, G. K., Rodrigo, A. G., & Solomon, W. (2002) · Genetics · doi:10.1093/genetics/161.3.1307 · Cited by 1,059
Cited by
Sorted by citations
A roadmap for the computation of persistent homology
Otter, N., Porter, M. A., Tillmann, U., Grindrod, P., & Harrington, H. A. (2017) · EPJ Data Science · doi:10.1140/epjds/s13688-017-0109-5 · Cited by 769
Homological scaffolds of brain functional networks
Petri, G., Expert, P., Turkheimer, F., Carhart-Harris, R., Nutt, D., Hellyer, P. J., & Vaccarino, F. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0873 · Cited by 675
Two’s company, three (or more) is a simplex
Giusti, C., Ghrist, R., & Bassett, D. S. (2016) · Journal of Computational Neuroscience · doi:10.1007/s10827-016-0608-6 · Cited by 426
What are higher-order networks?
Bick, C., Gross, E., Harrington, H. A., & Schaub, M. T. (2023) · SIAM Review · doi:10.1137/21m1414024 · Cited by 420
Clique topology reveals intrinsic geometric structure in neural correlations
Giusti, C., Pastalkova, E., Curto, C., & Itskov, V. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1506407112 · Cited by 381
Cliques and cavities in the human connectome
Sizemore, A. E., Giusti, C., Kahn, A. E., Vettel, J. M., Betzel, R. F., & Bassett, D. S. (2017) · Journal of Computational Neuroscience · doi:10.1007/s10827-017-0672-6 · Cited by 384
Rizvi, A. H., Camara, P. G., Kandror, E. K., Roberts, T. J., Schieren, I., Maniatis, T., & Rabadan, R. (2017) · Nature Biotechnology · doi:10.1038/nbt.3854 · Cited by 248
Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms
Hughes, D., & Andersson, D. I. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3922 · Cited by 249
Topological pattern recognition for point cloud data
Carlsson, G. (2014) · Acta Numerica · doi:10.1017/s0962492914000051 · Cited by 230
Self-citationRandom Walks on Simplicial Complexes and the Normalized Hodge 1-Laplacian
Schaub, M. T., Benson, A. R., Horn, P., Lippner, G., & Jadbabaie, A. (2020) · SIAM Review · doi:10.1137/18m1201019 · Cited by 268
Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions
Phinyomark, A., Petri, G., Ibáñez‐Marcelo, E., Osis, S. T., & Ferber, R. (2017) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-017-0297-2 · Cited by 175
Topological data analysis in biomedicine: A review
Skaf, Y., & Laubenbacher, R. (2022) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2022.104082 · Cited by 192
Simplicial complexes and complex systems
Salnikov, V., Cassese, D., & Lambiotte, R. (2018) · European Journal of Physics · doi:10.1088/1361-6404/aae790 · Cited by 164
A User’s Guide to Topological Data Analysis
Munch, E. (2017) · Journal of Learning Analytics · doi:10.18608/jla.2017.42.6 · Cited by 163
Persistent Homology Analysis for Materials Research and Persistent Homology Software: HomCloud
Obayashi, I., Nakamura, T., & Hiraoka, Y. (2022) · Journal of the Physical Society of Japan · doi:10.7566/jpsj.91.091013 · Cited by 149
Chatter detection in turning using persistent homology
Khasawneh, F. A., & Munch, E. (2015) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2015.09.046 · Cited by 141
Adaptive Genetic Exchange: A Tangled History of Admixture and Evolutionary Innovation
Arnold, M. L., & Kunte, K. K. (2017) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2017.05.007 · Cited by 135
Persistence diagrams with linear machine learning models
Obayashi, I., Hiraoka, Y., & Kimura, M. (2018) · Journal of Applied and Computational Topology · doi:10.1007/s41468-018-0013-5 · Cited by 123
Topological Data Analysis with Applications
Carlsson, G., & Vejdemo‐Johansson, M. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108975704 · Cited by 122
Self-citationThe ring of algebraic functions on persistence bar codes
Adcock, A., Carlsson, E., & Carlsson, G. (2016) · Homology Homotopy and Applications · doi:10.4310/hha.2016.v18.n1.a21 · Cited by 124
Self-citationPatania, A., Vaccarino, F., & Petri, G. (2017) · EPJ Data Science · doi:10.1140/epjds/s13688-017-0104-x · Cited by 106
Nielson, J. L., Cooper, S. R., Yue, J. K., Sorani, M. D., Inoue, T., Yuh, E. L., Mukherjee, P., Petrossian, T. C., Paquette, J., Lum, P. Y., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169490 · Cited by 100
Self-citationOyama, A., Hiraoka, Y., Obayashi, I., Saikawa, Y., Furui, S., Shiraishi, K., Kumagai, S., Hayashi, T., & Kotoku, J. (2019) · Scientific Reports · doi:10.1038/s41598-019-45283-z · Cited by 100
The shape of things to come: Topological data analysis and biology, from molecules to organisms
Amézquita, E. J., Quigley, M., Ophelders, T., Munch, E., & Chitwood, D. H. (2020) · Developmental Dynamics · doi:10.1002/dvdy.175 · Cited by 95
Construction of and efficient sampling from the simplicial configuration model
Young, J.-G., Petri, G., Vaccarino, F., & Patania, A. (2017) · Physical review. E · doi:10.1103/physreve.96.032312 · Cited by 84
Characterisation of the Idiotypic Immune Network Through Persistent Entropy
Rucco, M., Castiglione, F., Merelli, E., & Pettini, M. (2016) · Springer proceedings in complexity · doi:10.1007/978-3-319-29228-1_11 · Cited by 80
Offroy, M., & Duponchel, L. (2016) · Analytica Chimica Acta · doi:10.1016/j.aca.2015.12.037 · Cited by 80
Topological methods for data modelling
Carlsson, G. (2020) · Nature Reviews Physics · doi:10.1038/s42254-020-00249-3 · Cited by 85
Self-citationGraudenzi, A., Maspero, D., Angaroni, F., Piazza, R., & Ramazzotti, D. (2021) · iScience · doi:10.1016/j.isci.2021.102116 · Cited by 76
Transmission of influenza reflects seasonality of wild birds across the annual cycle
Hill, N. J., Ma, E. J., Meixell, B. W., Lindberg, M. S., Boyce, W. M., & Runstadler, J. A. (2016) · Ecology Letters · doi:10.1111/ele.12629 · Cited by 75
Algebraic stability of zigzag persistence modules
Botnan, M. B., & Lesnick, M. (2018) · Algebraic & Geometric Topology · doi:10.2140/agt.2018.18.3133 · Cited by 90
Inference of Ancestral Recombination Graphs through Topological Data Analysis
Cámara, P. G., Levine, A. J., & Rabadán, R. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005071 · Cited by 71
Volume-Optimal Cycle: Tightest Representative Cycle of a Generator in Persistent Homology
Obayashi, I. (2018) · SIAM Journal on Applied Algebra and Geometry · doi:10.1137/17m1159439 · Cited by 72
Global Patterns of Recombination across Human Viruses
Patiño-Galindo, J. Á., Filip, I., & Rabadán, R. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab046 · Cited by 67
Simplicial complexes and complex systems
Salnikov, V., Cassese, D., & Lambiotte, R. (2019) · Apollo (University of Cambridge) · doi:10.17863/cam.56775 · Cited by 63
Contagion in simplicial complexes
Li, Z., Deng, Z., Han, Z. Y., Alfaro-Bittner, K., Barzel, B., & Boccaletti, S. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111307 · Cited by 60
Topological Characterization of Complex Systems: Using Persistent Entropy
Merelli, E., Rucco, M., Sloot, P. M. A., & Tesei, L. (2015) · Entropy · doi:10.3390/e17106872 · Cited by 60
Topological data analysis for the string landscape
Cole, A., & Shiu, G. (2019) · Journal of High Energy Physics · doi:10.1007/jhep03(2019)054 · Cited by 60
Identification of relevant genetic alterations in cancer using topological data analysis
Rabadán, R., Mohamedi, Y., Rubin, U., Chu, T., Alghalith, A. N., Elliott, O., Arnes, L., Cal, S., Obaya, Á. J., Levine, A. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17659-7 · Cited by 56
Topological methods for genomics: Present and future directions
Cámara, P. G. (2016) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2016.12.007 · Cited by 55
Topological classifier for detecting the emergence of epileptic seizures
Piangerelli, M., Rucco, M., Tesei, L., & Merelli, E. (2018) · BMC Research Notes · doi:10.1186/s13104-018-3482-7 · Cited by 56
Binchi, J., Merelli, E., Rucco, M., Petri, G., & Vaccarino, F. (2014) · Electronic Notes in Theoretical Computer Science · doi:10.1016/j.entcs.2014.06.011 · Cited by 54
Stratifying Multiparameter Persistent Homology
Harrington, H. A., Otter, N., Schenck, H., & Tillmann, U. (2019) · SIAM Journal on Applied Algebra and Geometry · doi:10.1137/18m1224350 · Cited by 52
Lung Topology Characteristics in patients with Chronic Obstructive Pulmonary Disease
Guillamon, F. B., Pirashvili, M., Conway, J. H., Bennett, M. J., Djukanović, R., & Brodzki, J. (2018) · Scientific Reports · doi:10.1038/s41598-018-23424-0 · Cited by 54
Topological Data Analysis Generates High-Resolution, Genome-wide Maps of Human Recombination
Cámara, P. G., Rosenbloom, D. I. S., Emmett, K., Levine, A. J., & Rabadán, R. (2016) · Cell Systems · doi:10.1016/j.cels.2016.05.008 · Cited by 50
Topological portraits of multiscale coordination dynamics
Zhang, M., Kalies, W. D., Kelso, J. A. S., & Tognoli, E. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108672 · Cited by 49
Multidimensional Persistence and Noise
Scolamiero, M., Chachólski, W., Lundman, A., Ramanujam, R., & Öberg, S. (2016) · Foundations of Computational Mathematics · doi:10.1007/s10208-016-9323-y · Cited by 48
Parametric Inference using Persistence Diagrams: A Case Study in Population GeneticsPreprint
Emmett, K., Rosenbloom, D. I. S., Cámara, P. G., & Rabadán, R. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1406.4582 · Cited by 47
An introduction to multiparameter persistence
Botnan, M. B., & Lesnick, M. (2023) · EMS series of congress reports · doi:10.4171/ecr/19/4 · Cited by 45
The persistence of large scale structures. Part I. Primordial non-Gaussianity
Biagetti, M., Cole, A., & Shiu, G. (2021) · Journal of Cosmology and Astroparticle Physics · doi:10.1088/1475-7516/2021/04/061 · Cited by 45
Giusti, C., Ghrist, R., & Bassett, D. S. (2016) · PubMed Central · doi:10.48550/arxiv.1601.01704 · Cited by 44
F-Mapper: A Fuzzy Mapper clustering algorithm
Bui, Q., Vo, B., Nguyen, H.-A. T., Nguyen, Q. V. H., & Snåšel, V. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.105107 · Cited by 44
The topology of data: opportunities for cancer research
Loughrey, C. F., Fitzpatrick, P., Orr, N., & Jurek, A. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab553 · Cited by 44
Persistent Homology Machine Learning for Fingerprint Classification
Giansiracusa, N., Giansiracusa, R., & Moon, C. (2019) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2019.00201 · Cited by 42
Universality of the homotopy interleaving distance
Blumberg, A. J., & Lesnick, M. (2022) · Transactions of the American Mathematical Society · doi:10.1090/tran/8738 · Cited by 42
Takahashi, K., Abe, K., Kubota, S. I., Fukatsu, N., Morishita, Y., Yoshimatsu, Y., Hirakawa, S., Kubota, Y., Watabe, T., Ehata, S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32848-2 · Cited by 45
Unveiling patterns of international communities in a global city using mobile phone data
Bajardi, P., Delfino, M., Panisson, A., Petri, G., & Tizzoni, M. (2015) · EPJ Data Science · doi:10.1140/epjds/s13688-015-0041-5 · Cited by 40
Identification of Topological Network Modules in Perturbed Protein Interaction Networks
Sardiu, M. E., Gilmore, J. M., Groppe, B. D., Florens, L. A., & Washburn, M. P. (2017) · Scientific Reports · doi:10.1038/srep43845 · Cited by 40
Quantitative and interpretable order parameters for phase transitions from persistent homology
Cole, A., Loges, G. J., & Shiu, G. (2021) · Physical review. B./Physical review. B · doi:10.1103/physrevb.104.104426 · Cited by 45
Yoo, J., Kim, E. Y., Ahn, Y. M., & Ye, J. C. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.04.001 · Cited by 43
Acridine Derivatives as Inhibitors of the IRE1α–XBP1 Pathway Are Cytotoxic to Human Multiple Myeloma
Jiang, D., Tam, A. B., Alagappan, M., Hay, M. P., Gupta, A., Kozak, M. M., Solow-Cordero, D. E., Lum, P. Y., Denko, N. C., Giaccia, A. J., et al. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-15-1023 · Cited by 36
Exploring hyperspectral imaging data sets with topological data analysis
Duponchel, L. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.11.029 · Cited by 36
Assessment of skin barrier function using skin images with topological data analysis
Koseki, K., Kawasaki, H., Atsugi, T., Nakanishi, M., Mizuno, M., Naru, E., Ebihara, T., Amagai, M., & Kawakami, E. (2020) · npj Systems Biology and Applications · doi:10.1038/s41540-020-00160-8 · Cited by 36
Clustering-independent analysis of genomic data using spectral simplicial theory
Govek, K. W., Yamajala, V. S., & Camara, P. G. (2019) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1007509 · Cited by 33
Noise-driven topological changes in chaotic dynamics
Charó, G. D., Chekroun, M. D., Sciamarella, D., & Ghil, M. (2021) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0059461 · Cited by 35
Greening, B., Pinter‐Wollman, N., & Fefferman, N. H. (2015) · Current Zoology · doi:10.1093/czoolo/61.1.114 · Cited by 34
Modeling and replicating statistical topology and evidence for CMB nonhomogeneity
Adler, R. J., Agami, S., & Pranav, P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706885114 · Cited by 34
Locating a Tree in a Phylogenetic Network in Quadratic Time
Gambette, P., Gunawan, A. D. M., Labarre, A., Vialette, S., & Zhang, L. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16706-0_12 · Cited by 33
Liao, T., Wei, Y., Luo, M., Zhao, G., & Zhou, H. (2019) · Genome biology · doi:10.1186/s13059-019-1871-4 · Cited by 31
Multiscale Topology of Chromatin Folding
Emmett, K., Schweinhart, B., & Rabadán, R. (2016) · International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS) · doi:10.4108/eai.3-12-2015.2262453 · Cited by 36
The diversity, evolution and epidemiology of plant viruses: A phylogenetic view
Pagán, I. (2018) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2018.07.033 · Cited by 31
A decomposition theorem and two algorithms for reticulation-visible networks
Gunawan, A. D. M., DasGupta, B., & Zhang, L. (2016) · Information and Computation · doi:10.1016/j.ic.2016.11.001 · Cited by 30
Persistent homology and applied homotopy theory
Carlsson, G. (2020) · Chapman & Hall/CRC eBooks · doi:10.1201/9781351251624-8 · Cited by 30
Self-citationTopological data analysis model for the spread of the coronavirus
Chen, Y., & Volić, I. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255584 · Cited by 30
Ramazzotti, D., Angaroni, F., Maspero, D., Gambacorti-Passerini, C. B., Antoniotti, M., Graudenzi, A., & Piazza, R. (2021) · Patterns · doi:10.1016/j.patter.2021.100212 · Cited by 29
A kernel for multi-parameter persistent homology
Corbet, R., Fugacci, U., Kerber, M., Landi, C., & Wang, B. (2019) · Computers & Graphics X · doi:10.1016/j.cagx.2019.100005 · Cited by 30
A Review of Topological Data Analysis and Topological Deep Learning in Molecular Sciences
Wee, J., & Jiang, J. W. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c02266 · Cited by 36
Viral evolution: beyond drift and shift
Greenbaum, B. D., & Ghedin, E. (2015) · Current Opinion in Microbiology · doi:10.1016/j.mib.2015.06.015 · Cited by 28
Approximating persistent homology in Euclidean space through collapses
Botnan, M. B., & Spreemann, G. (2015) · Applicable Algebra in Engineering Communication and Computing · doi:10.1007/s00200-014-0247-y · Cited by 27
Possible pandemic threat from new reassortment of influenza A(H7N9) virus in China
Meng, Z., Han, R., Hu, Y., Yuan, Z., Jiang, S., Zhang, X., & Xu, J. (2014) · Eurosurveillance · doi:10.2807/1560-7917.es2014.19.6.20699 · Cited by 27
Fast Estimation of Recombination Rates Using Topological Data Analysis
Humphreys, D. P., McGuirl, M. R., Miyagi, M., & Blumberg, A. J. (2019) · Genetics · doi:10.1534/genetics.118.301565 · Cited by 25
Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
Ibekwe, A. M., Ma, J., Crowley, D. E., Yang, C., Johnson, A. M., Petrossian, T. C., & Lum, P. Y. (2014) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2014.00122 · Cited by 24
Suzuki, A., Miyazawa, M., Okamoto, A., Shimizu, H., Obayashi, I., Hiraoka, Y., Tsuji, T., Kang, P. K., & Ito, T. (2020) · Computers & Geosciences · doi:10.1016/j.cageo.2020.104550 · Cited by 24
Salch, A., Regalski, A., Abdallah, H., Suryadevara, R., Catanzaro, M. J., & Diwadkar, V. A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255859 · Cited by 30
Fisher forecasts for primordial non-Gaussianity from persistent homology
Biagetti, M., Calles, J., Castiblanco, L., Cole, A., & Noreña, J. (2022) · Journal of Cosmology and Astroparticle Physics · doi:10.1088/1475-7516/2022/10/002 · Cited by 24
Amézquita, E. J., Quigley, M., Ophelders, T., Landis, J. B., Koenig, D., Munch, E., & Chitwood, D. H. (2021) · in silico Plants · doi:10.1093/insilicoplants/diab033 · Cited by 24
Multiscale Projective Coordinates via Persistent Cohomology of Sparse Filtrations
Perea, J. A. (2017) · Discrete & Computational Geometry · doi:10.1007/s00454-017-9927-2 · Cited by 27
Persistent Cohomology for Data With Multicomponent Heterogeneous Information
Cang, Z., & Wei, G. (2020) · SIAM Journal on Mathematics of Data Science · doi:10.1137/19m1272226 · Cited by 27
Li, L., Thompson, C., Henselman‐Petrusek, G., Giusti, C., & Ziegelmeier, L. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.681117 · Cited by 22
Multiplex Financial Networks: Revealing the Level of Interconnectedness in the Banking System
de la Concha, A., Martínez-Jaramillo, S., & Carmona, C. U. (2017) · Studies in computational intelligence · doi:10.1007/978-3-319-72150-7_92 · Cited by 21
Topological data analysis to model the shape of immune responses during co-infections
Sasaki, K., Bruder, D., & Hernandez-Vargas, E. A. (2020) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2020.105228 · Cited by 21
A universal null-distribution for topological data analysis
Bobrowski, O., & Škraba, P. (2023) · Scientific Reports · doi:10.1038/s41598-023-37842-2 · Cited by 38
Topological data analysis and topological deep learning beyond persistent homology: a review
Su, Z., Liu, X., Hamdan, L. B., Maroulas, V., Wu, J., Carlsson, G., & Wei, G.-W. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11462-w · Cited by 38
Self-citationStable volumes for persistent homology
Obayashi, I. (2023) · Journal of Applied and Computational Topology · doi:10.1007/s41468-023-00119-8 · Cited by 20
Persistent homology and string vacua
Cirafici, M. (2016) · Journal of High Energy Physics · doi:10.1007/jhep03(2016)045 · Cited by 20
Evolving Perspective on the Origin and Diversification of Cellular Life and the Virosphere
Spang, A., Mahendrarajah, T., Offre, P., & Stairs, C. W. (2022) · Genome Biology and Evolution · doi:10.1093/gbe/evac034 · Cited by 19
What cannot be seen correctly in 2D visualizations of single-cell ‘omics data?
Wang, S., Sontag, E. D., & Lauffenburger, D. A. (2023) · Cell Systems · doi:10.1016/j.cels.2023.07.002 · Cited by 19
Solving the tree containment problem in linear time for nearly stable phylogenetic networks
Gambette, P., Gunawan, A. D. M., Labarre, A., Vialette, S., & Zhang, L. (2017) · Discrete Applied Mathematics · doi:10.1016/j.dam.2017.07.015 · Cited by 19
On homotopy types of Vietoris–Rips complexes of metric gluings
Adamaszek, M., Adams, H., Gasparovic, E., Gommel, M., Purvine, E., Sazdanović, R., Wang, B., Wang, Y., & Ziegelmeier, L. (2020) · Journal of Applied and Computational Topology · doi:10.1007/s41468-020-00054-y · Cited by 19
Tropical Sufficient Statistics for Persistent Homology
Monod, A., Kališnik, S., Patiño-Galindo, J. Á., & Crawford, L. A. (2019) · SIAM Journal on Applied Algebra and Geometry · doi:10.1137/17m1148037 · Cited by 18
Metadata
- Authors
- Chan, J. M., Carlsson, G., & Rabadan, R.
- Affiliations
- Columbia University (US)
- Stanford University (US)
- Center for Computational Biology and Bioinformatics and
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-10-29
- Volume
- 110
- Issue
- 46
- Pages
- 18566-18571
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3831954
- OpenAlex
- W2107385756
- Cited by
- 269
- References
- 46
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 15 · 2023: 27 · 2022: 14 · 2021: 37 · 2020: 28 · 2019: 23 · 2018: 18 · 2017: 29 · 2016: 27 · 2015: 18 · 2014: 10 · 2013: 1
- FWCI
- 12.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (0905823, 0964242)
- National Institutes of Health (W81XWH, CA121852, U54-CA121852)
- National Cancer Institute (U54CA121852, U54CA149145, I-U54_CA149145-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Keywords
- reticulate evolution, viral evolution, algebraic topology, phylogenetic tree, reassortment, recombination, RNA viruses, H7N9 avian influenza, HIV-1 recombinants, clonal evolution
- MeSH terms
- Base Sequence, Classification, Computer Simulation, Models, Genetic, Phylogeny, HIV-1, Reassortant Viruses, Sequence Homology, Evolution, Molecular, Computational Biology, Gene Transfer, Horizontal, Principal Component Analysis, Influenza A Virus, H1N1 Subtype, Molecular Sequence Annotation, Influenza A Virus, H7N9 Subtype
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review