Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

Abstract

an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

Full text

Its licence does not allow us to show the full text. Read it at PubMed Central:

References 210

1. 1.

   Tonegawa S. Somatic generation of antibody diversity. Nature (1983 ) 302:575–81.

   Not in our library10.1038/302575a0

2. 2.

   Wardemann H Busse CE. Novel approaches to analyze immunoglobulin repertoires. Trends Immunol (2017 ) 38(7):471–82.

   Not in our library10.1016/j.it.2017.05.003

3. 3.

   Glanville J Zhai W Berka J Telman D Huerta G Mehta GR Precise determination of the diversity of a combinatorial antibody library gives insight into the human immunoglobulin repertoire. Proc Natl Acad Sci U S A (2009 ) 106:20216–21.

   Not in our library10.1073/pnas.0909775106

4. 4.
   Inferring processes underlying B-cell repertoire diversity · 2015

   No notice
5. 5.

   Murugan A Mora T Walczak AM Callan CG Statistical inference of the generation probability of T-cell receptors from sequence repertoires. Proc Natl Acad Sci U S A (2012 ) 109:16161–6.

   Not in our library10.1073/pnas.1212755109

6. 6.

   Greiff V Menzel U Miho E Weber C Riedel R Cook S Systems analysis reveals high genetic and antigen-driven predetermination of antibody repertoires throughout B cell development. Cell Rep (2017 ) 19:1467–78.

   Not in our library10.1016/j.celrep.2017.04.054

7. 7.

   Burnet FM Theories of immunity. Perspect Biol Med (1960 ) 3:447–58.

   Not in our library10.1353/pbm.1960.0034

8. 8.

   Ahmed R Gray D. Immunological memory and protective immunity: understanding their relation. Science (1996 ) 272:54–60.

   Not in our library10.1126/science.272.5258.54

9. 9.

   Hammarlund E Lewis MW Carter SV Amanna I Hansen SG Strelow LI Multiple diagnostic techniques identify previously vaccinated individuals with protective immunity against monkeypox. Nat Med (2005 ) 11:1005–11.

   Not in our library10.1038/nm1273

10. 10.

    Amanna IJ Carlson NE Slifka MK. Duration of humoral immunity to common viral and vaccine antigens. N Engl J Med (2007 ) 357:1903–15.

    Not in our library10.1056/nejmoa066092

11. 11.

    Manz RA Thiel A Radbruch A Lifetime of plasma cells in the bone marrow. Nature (1997 ) 388:133–4.

    Not in our library10.1038/40540

12. 12.

    Landsverk OJB Snir O Casado RB Richter L Mold JE Réu P Antibody-secreting plasma cells persist for decades in human intestine. J Exp Med (2017 ) 214(2):309–17.

    Not in our library10.1084/jem.20161590

13. 13.

    Halliley JL Tipton CM Liesveld J Rosenberg AF Darce J Gregoretti IV Long-lived plasma cells are contained within the CD19−CD38hiCD138+ subset in human bone marrow. Immunity (2015 ) 43(1):132–45.

    Not in our library10.1016/j.immuni.2015.06.016

14. 14.
    The chronically inflamed central nervous system provides niches for long-lived plasma cells · 2017

    Not checked
15. 15.

    Calis JJA Rosenberg BR. Characterizing immune repertoires by high throughput sequencing: strategies and applications. Trends Immunol (2014 ) 35:581–90.

    Not in our library10.1016/j.it.2014.09.004

16. 16.

    Georgiou G Ippolito GC Beausang J Busse CE Wardemann H Quake SR. The promise and challenge of high-throughput sequencing of the antibody repertoire. Nat Biotechnol (2014 ) 32:158–68.

    Not in our library10.1038/nbt.2782

17. 17.

    Greiff V Miho E Menzel U Reddy ST. Bioinformatic and statistical analysis of adaptive immune repertoires. Trends Immunol (2015 ) 36:738–49.

    Not in our library10.1016/j.it.2015.09.006

18. 18.

    Baum PD Venturi V Price DA. Wrestling with the repertoire: the promise and perils of next generation sequencing for antigen receptors. Eur J Immunol (2012 ) 42:2834–9.

    Not in our library10.1002/eji.201242999

19. 19.

    Robinson WH Sequencing the functional antibody repertoire—diagnostic and therapeutic discovery. Nat Rev Rheumatol (2014 ) 11:171–82.

    Not in our library10.1038/nrrheum.2014.220

20. 20.

    Cobey S Wilson P Matsen FA. The evolution within us. Philos Trans R Soc Lond B Biol Sci (2015 ) 370:20140235.

    Not in our library10.1098/rstb.2014.0235

21. 21.

    Weinstein JA Jiang N White RA Fisher DS Quake SR. High-throughput sequencing of the zebrafish antibody repertoire. Science (2009 ) 324:807–10.

    Not in our library10.1126/science.1170020

22. 22.
    A Public Database of Memory and Naive B-Cell Receptor Sequences · 2016

    No notice
23. 23.

    Kidd BA Peters LA Schadt EE Dudley JT. Unifying immunology with informatics and multiscale biology. Nat Immunol (2014 ) 15:118–27.

    Not in our library10.1038/ni.2787

24. 24.
    Practical guidelines for B-cell receptor repertoire sequencing analysis · 2015

    No notice
25. 25.

    Janeway CA Murphy K Janeway’s Immunobiology. 8th Revised Edition Taylor & Francis (2011 ).

    Not in our library

26. 26.

    Watson CT Steinberg KM Huddleston J Warren RL Malig M Schein J Complete haplotype sequence of the human immunoglobulin heavy-chain variable, diversity, and joining genes and characterization of allelic and copy-number variation. Am J Hum Genet (2013 ) 92(4):530–46.

    Not in our library10.1016/j.ajhg.2013.03.004

27. 27.

    Johnston CM Wood AL Bolland DJ Corcoran AE. Complete sequence assembly and characterization of the C57BL/6 mouse Ig heavy chain V region. J Immunol (2006 ) 176:4221–34.

    Not in our library10.4049/jimmunol.176.7.4221

28. 28.

    Malissen M Minard K Mjolsness S Kronenberg M Goverman J Hunkapiller T Mouse T cell antigen receptor: Structure and organization of constant and joining gene segments encoding the β polypeptide. Cell (1984 ) 37:1101–10.

    Not in our library10.1016/0092-8674(84)90444-6

29. 29.

    Arden B Clark SP Kabelitz D Mak TW. Human T-cell receptor variable gene segment families. Immunogenetics (1995 ) 42:455–500.

    Not in our library10.1007/bf00172176

30. 30.

    Watson CT Glanville J Marasco WA. The individual and population genetics of antibody immunity. Trends Immunol (2017 ) 38(7):459–70.

    Not in our library10.1016/j.it.2017.04.003

31. 31.

    Trepel F Number and distribution of lymphocytes in man. A critical analysis. J Mol Med (1974 ) 52:511–5.

    Not in our library10.1007/bf01468720

32. 32.

    Granato A Chen Y Wesemann DR. Primary immunoglobulin repertoire development: time and space matter. Curr Opin Immunol (2015 ) 33:126–31.

    Not in our library10.1016/j.coi.2015.02.011

33. 33.

    Breden F Prak Luning TE Peters B Rubelt F Schramm CA Busse CE Reproducibility and reuse of adaptive immune receptor repertoire data. Front Immunol (2017 ) 8:1418.

    Not in our library10.3389/fimmu.2017.01418

34. 34.

    Rubelt F Busse CE Bukhari SAC Bürckert J-P Mariotti-Ferrandiz E Cowell LG Adaptive immune receptor repertoire community recommendations for sharing immune-repertoire sequencing data. Nat Immunol (2017 ) 18(12):1274–8.

    Not in our library10.1038/ni.3873

35. 35.
    IGHV1-69 polymorphism modulates anti-influenza antibody repertoires, correlates with IGHV utilization shifts and varies by ethnicity · 2016

    Corrected
36. 36.
    Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity · 2016

    No notice
37. 37.

    Gadala-Maria D Yaari G Uduman M Kleinstein SH. Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles. Proc Natl Acad Sci U S A (2015 ) 112:E862–70.

    Not in our library10.1073/pnas.1417683112

38. 38.

    Ralph DK Matsen FA IV Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data. Q-Bio (2017 ). Available from http://arxiv.org/abs/1711.05843

    Not in our library10.1371/journal.pcbi.1007133

39. 39.

    Boyd SD Gaëta BA Jackson KJ Fire AZ Marshall EL Merker JD Individual variation in the germline Ig gene repertoire inferred from variable region gene rearrangements. J Immunol (2010 ) 184:6986–92.

    Not in our library10.4049/jimmunol.1000445

40. 40.

    Kidd MJ Chen Z Wang Y Jackson KJ Zhang L Boyd SD The inference of phased haplotypes for the immunoglobulin H chain V region gene loci by analysis of VDJ gene rearrangements. J Immunol Baltim (2012 ) 188:1333–40.

    Not in our library10.4049/jimmunol.1102097

41. 41.

    Kirik U Greiff L Levander F Ohlin M Parallel antibody germline gene and haplotype analyses support the validity of immunoglobulin germline gene inference and discovery. Mol Immunol (2017 ) 87:12–22.

    Not in our library10.1016/j.molimm.2017.03.012

42. 42.

    Yu Y Ceredig R Seoighe C. A Database of human immune receptor alleles recovered from population sequencing data. J Immunol (2017 ) 198(5):2202–10.

    Not in our library10.4049/jimmunol.1601710

43. 43.

    Watson CT Matsen FA Jackson KJL Bashir A Smith ML Glanville J Comment on “a database of human immune receptor alleles recovered from population sequencing data”. J Immunol (2017 ) 198:3371–3.

    Not in our library10.4049/jimmunol.1700306

44. 44.

    Giudicelli V Chaume D Lefranc M-P. IMGT/V-QUEST, an integrated software program for immunoglobulin and T cell receptor V-J and V-D-J rearrangement analysis. Nucleic Acids Res (2004 ) 32:W435–40.

    Not in our library10.1093/nar/gkh412

45. 45.

    Elhanati Y Marcou Q Mora T Walczak AM. repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data. Bioinformatics (2016 ) 32:1943–51.

    Not in our library10.1093/bioinformatics/btw112

46. 46.
    Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation · 2016

    No notice
47. 47.
    High-throughput immune repertoire analysis with IGoR · 2018

    No notice
48. 48.

    Glanville J Kuo TC von Büdingen H-C Guey L Berka J Sundar PD Naive antibody gene-segment frequencies are heritable and unaltered by chronic lymphocyte ablation. Proc Natl Acad Sci U S A (2011 ) 108:20066–71.

    Not in our library10.1073/pnas.1107498108

49. 49.

    Reddy ST Ge X Miklos AE Hughes RA Kang SH Hoi KH Monoclonal antibodies isolated without screening by analyzing the variable-gene repertoire of plasma cells. Nat Biotechnol (2010 ) 28:965–9.

    Not in our library10.1038/nbt.1673

50. 50.
    Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen-experienced cells · 2016

    No notice
51. 51.

    Shugay M Bolotin DA Putintseva EV Pogorelyy MV Mamedov IZ Chudakov DM Huge overlap of individual TCR beta repertoires. T Cell Biol (2013 ) 4:466

    Not in our library10.3389/fimmu.2013.00466

52. 52.
    System-wide Analysis of the T Cell Response · 2016

    Not checked
53. 53.

    Madi A Shifrut E Reich-Zeliger S Gal H Best K Ndifon W T-cell receptor repertoires share a restricted set of public and abundant CDR3 sequences that are associated with self-related immunity. Genome Res (2014 ) 24:1603–12.

    Not in our library10.1101/gr.170753.113

54. 54.

    Collins AM Jackson KJL. On being the right size: antibody repertoire formation in the mouse and human. Immunogenetics (2017 ).

    Not in our library10.1007/s00251-017-1049-8

55. 55.

    Castro R Navelsaker S Krasnov A Du Pasquier L Boudinot P. Describing the diversity of Ag specific receptors in vertebrates: contribution of repertoire deep sequencing. Dev Comp Immunol (2017 ) 75:28–37.

    Not in our library10.1016/j.dci.2017.02.018

56. 56.

    Elhanati Y Murugan A Callan CG Mora T Walczak AM. Quantifying selection in immune receptor repertoires. Proc Natl Acad Sci U S A (2014 ) 111:9875–80.

    Not in our library10.1073/pnas.1409572111

57. 57.

    Pogorelyy MV Minervina AA Chudakov DM Mamedov IZ Lebedev YB Mora T Method for identification of condition-associated public antigen receptor sequences. Q-Bio (2017 ). Available from: http://arxiv.org/abs/1709.09703

    Not in our library10.7554/elife.33050

58. 58.

    Greiff V Weber CR Palme J Bodenhofer U Miho E Menzel U Learning the high-dimensional immunogenomic features that predict public and private antibody repertoires. J Immunol (2017 ) 199:2985–97.

    Not in our library10.4049/jimmunol.1700594

59. 59.

    Jost L Entropy and diversity. Oikos (2006 ) 113:363–75.

    Not in our library10.1111/j.2006.0030-1299.14714.x

60. 60.

    Rempala GA Seweryn M. Methods for diversity and overlap analysis in T-cell receptor populations. J Math Biol (2013 ) 67:1–30.

    Not in our library10.1007/s00285-012-0589-7

61. 61.

    Venturi V Kedzierska K Tanaka MM Turner SJ Doherty PC Davenport MP. Method for assessing the similarity between subsets of the T cell receptor repertoire. J Immunol Methods (2008 ) 329:67–80.

    Not in our library10.1016/j.jim.2007.09.016

62. 62.

    Venturi V Kedzierska K Turner SJ Doherty PC Davenport MP. Methods for comparing the diversity of samples of the T cell receptor repertoire. J Immunol Methods (2007 ) 321:182–95.

    Not in our library10.1016/j.jim.2007.01.019

63. 63.

    Hershberg U Prak ETL. The analysis of clonal expansions in normal and autoimmune B cell repertoires. Phil Trans R Soc Lond B Biol Sci (2015 ) 370:20140239.

    Not in our library10.1098/rstb.2014.0239

64. 64.

    Nouri N Kleinstein SH Performance-optimized partitioning of clonotypes from high-throughput immunoglobulin repertoire sequencing data. bioRxiv (2017 ).

    Not in our library10.1101/175315

65. 65.
    A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status · 2015

    No notice
66. 66.

    Gupta NT Heiden JV Uduman M Gadala-Maria D Yaari G Kleinstein SH. Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics (2015 ) 31(20):3356–8.

    Not in our library10.1093/bioinformatics/btv359

67. 67.

    Oksanen J Blanchet FG Kindt R Legendre P Minchin PR O’Hara RB Vegan: Community Ecology Package. (2015 ). Available from: http://CRAN.R-project.org/package=vegan

    Not in our library

68. 68.
    tcR: an R package for T cell receptor repertoire advanced data analysis · 2015

    No notice
69. 69.
    VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires · 2015

    No notice
70. 70.

    Solomon DL Unit CUB, Biometrics CUD of, Biology CUD of BS and C. Biometrics Unit Technical Reports: Number BU-573-M: A Comparative Approach to Species Diversity. (1975 ). Available from: http://ecommons.library.cornell.edu/handle/1813/32672

    Not in our library

71. 71.

    Snir O Mesin L Gidoni M Lundin KEA Yaari G Sollid LM. Analysis of celiac disease autoreactive gut plasma cells and their corresponding memory compartment in peripheral blood using high-throughput sequencing. J Immunol (2015 ) 194:5703–12.

    Not in our library10.4049/jimmunol.1402611

72. 72.

    Mora T Walczak AM Renyi entropy, abundance distribution and the equivalence of ensembles. ArXiv Prepr ArXiv160305458 (2016 ). Available from: http://arxiv.org/abs/1603.05458

    Not in our library10.1103/physreve.93.052418

73. 73.

    Afzal S Gil-Farina I Gabriel R Ahmad S von Kalle C Schmidt M Systematic comparative study of computational methods for T-cell receptor sequencing data analysis. Brief Bioinform (2017 ) 1–13.

    Not in our library10.1093/bib/bbx111

74. 74.

    Mora T Walczak AM Bialek W Callan CG. Maximum entropy models for antibody diversity. Proc Natl Acad Sci U S A (2010 ) 107:5405–10.

    Not in our library10.1073/pnas.1001705107

75. 75.

    Oakes T Heather JM Best K Byng-Maddick R Husovsky C Ismail M Quantitative characterization of the T cell receptor repertoire of naïve and memory subsets using an integrated experimental and computational pipeline which is robust, economical, and versatile. Front Immunol (2017 ) 8:1267

    Not in our library10.3389/fimmu.2017.01267

76. 76.

    Grigaityte K Carter JA Goldfless SJ Jeffery EW Hause RJ Jiang Y Single-cell sequencing reveals αβ chain pairing shapes the T cell repertoire. bioRxiv (2017 ).

    Not in our library10.1101/213462

77. 77.

    Schwab DJ Nemenman I Mehta P Zipf’s law and criticality in multivariate data without fine-tuning. Phys Rev Lett (2014 ) 113:068102

    Not in our library10.1103/physrevlett.113.068102

78. 78.

    Jackson KJL Liu Y Roskin KM Glanville J Hoh RA Seo K Human responses to influenza vaccination show seroconversion signatures and convergent antibody rearrangements. Cell Host Microbe (2014 ) 16:105–14.

    Not in our library10.1016/j.chom.2014.05.013

79. 79.

    Bolkhovskaya OV Zorin DY Ivanchenko MV. Assessing T cell clonal size distribution: a non-parametric approach. PLoS One (2014 ) 9:e108658.

    Not in our library10.1371/journal.pone.0108658

80. 80.

    Kaplinsky J Arnaout R. Robust estimates of overall immune-repertoire diversity from high-throughput measurements on samples. Nat Commun (2016 ) 7:11881.

    Not in our library10.1038/ncomms11881

81. 81.

    Chao A Shen T-J Nonparametric estimation of Shannon’s index of diversity when there are unseen species in sample. Environ Ecol Stat (2003 ) 10:429–43.

    Not in our library10.1023/a:1021993627070

82. 82.

    Laydon DJ Melamed A Sim A Gillet NA Sim K Darko S Quantification of HTLV-1 clonality and TCR diversity. PLoS Comput Biol (2014 ) 10:e1003646.

    Not in our library10.1371/journal.pcbi.1003646

83. 83.
    Estimating T-cell repertoire diversity: limitations of classical estimators and a new approach · 2015

    No notice
84. 84.

    Good IJ The population frequencies of species and the estimation of population parameters. Biometrika (1953 ) 40:237–64.

    Not in our library10.1093/biomet/40.3-4.237

85. 85.

    Stern JNH Yaari G Heiden JAV Church G Donahue WF Hintzen RQ B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Sci Transl Med (2014 ) 6:248ra107.

    Not in our library10.1126/scitranslmed.3008879

86. 86.

    Warren RL Freeman JD Zeng T Choe G Munro S Moore R Exhaustive T-cell repertoire sequencing of human peripheral blood samples reveals signatures of antigen selection and a directly measured repertoire size of at least 1 million clonotypes. Genome Res (2011 ) 21:790–7.

    Not in our library10.1101/gr.115428.110

87. 87.

    Meng W Zhang B Schwartz GW Rosenfeld AM Ren D Thome JJC An atlas of B-cell clonal distribution in the human body. Nat Biotechnol (2017 ) 35:879–84.

    Not in our library10.1038/nbt.3942

88. 88.

    Hochreiter S Schmidhuber J. Long short-term memory. Neural Comput (1997 ) 9:1735–80.

    Not in our library10.1162/neco.1997.9.8.1735

89. 89.
    Deep learning for computational biology · 2016

    No notice
90. 90.

    Stubbington MJT Rozenblatt-Rosen O Regev A Teichmann SA. Single-cell transcriptomics to explore the immune system in health and disease. Science (2017 ) 358:58–63.

    Not in our library10.1126/science.aan6828

91. 91.

    DeKosky B Paired VH:VL analysis of naïve B cell repertoires and comparison to antigen-experienced B cell repertoires in healthy human donors. Decoding the Antibody Repertoire, Springer Theses (Springer International Publishing) (2017 ). p. 41–57. https://www.nature.com/articles/nm.3743

    Not in our library

92. 92.

    DeKosky BJ Ippolito GC Deschner RP Lavinder JJ Wine Y Rawlings BM High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire. Nat Biotechnol (2013 ) 31:166–69.

    Not in our library10.1038/nbt.2492

93. 93.

    Howie B Sherwood AM Berkebile AD Berka J Emerson RO Williamson DW High-throughput pairing of T cell receptor α and β sequences. Sci Transl Med (2015 ) 7:ra131–301.

    Not in our library10.1126/scitranslmed.aac5624

94. 94.

    Miho E Greiff V Roskar R Reddy ST The fundamental principles of antibody repertoire architecture revealed by large-scale network analysis. bioRxiv (2017 ).

    Not in our library10.1101/124578

95. 95.

    Bashford-Rogers RJM Palser AL Huntly BJ Rance R Vassiliou GS Follows GA Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations. Genome Res (2013 ) 23:1874–84.

    Not in our library10.1101/gr.154815.113

96. 96.

    Ben-Hamo R Efroni S. The whole-organism heavy chain B cell repertoire from zebrafish self-organizes into distinct network features. BMC Syst Biol (2011 ) 5:27.

    Not in our library10.1186/1752-0509-5-27

97. 97.

    Chang Y-H Kuan H-C Hsieh TC Ma KH Yang C-H Hsu W-B Network signatures of IgG immune repertoires in hepatitis B associated chronic infection and vaccination responses. Sci Rep (2016 ) 6:26556.

    Not in our library10.1038/srep26556

98. 98.

    Hoehn KB Gall A Bashford-Rogers R Fidler SJ Kaye S Weber JN Dynamics of immunoglobulin sequence diversity in HIV-1 infected individuals. Phil Trans R Soc Lond B Biol Sci (2015 ) 370:20140241.

    Not in our library10.1098/rstb.2014.0241

99. 99.

    Lindner C Thomsen I Wahl B Ugur M Sethi MK Friedrichsen M Diversification of memory B cells drives the continuous adaptation of secretory antibodies to gut microbiota. Nat Immunol (2015 ) 16:880–8.

    Not in our library10.1038/ni.3213

100. 100.
     T cell receptor repertoires of mice and humans are clustered in similarity networks around conserved public CDR3 sequences · 2017

     No notice
101. 101.

     Lee SH Kim P-J Jeong H Statistical properties of sampled networks. Phys Rev E (2006 ) 73:016102

     Not in our library10.1103/physreve.73.016102

102. 102.

     Sethu H Chu X A new algorithm for extracting a small representative subgraph from a very large graph. Phys (2012 ). Available from: http://arxiv.org/abs/1207.4825

     Not in our library

103. 103.

     Csardi G Nepusz T The igraph software package for complex network research, complex system. InterJournal (2006 ) 1695.

     Not in our library

104. 104.

     Hagberg AA Schult DA Swart PJ Exploring network structure, dynamics, and function using networkx. In: Varoquaux G Vaught T Millman J, editors. Proceedings of the 7th Python in Science Conference (SciPy2008) Pasadena, CA USA (2008 ). p. 11–5.

     Not in our library

105. 105.

     Bastian M Heymann S Jacomy M Gephi: an open source software for exploring and manipulating networks. ICWSM (2009 ) 8:361–2.

     Not in our library

106. 106.

     Shannon P Markiel A Ozier O Baliga NS Wang JT Ramage D Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res (2003 ) 13:2498–504.

     Not in our library10.1101/gr.1239303

107. 107.

     Albert R Jeong H Barabasi A-L Error and attack tolerance of complex networks: article: nature. Nature (2000 ) 406:378–82.

     Not in our library10.1101/187120

108. 108.

     Barabási A-L Network science. Boston, USA: Cambridge University Press (2016 ).

     Not in our library

109. 109.

     Strauli NB Hernandez RD. Statistical inference of a convergent antibody repertoire response to influenza vaccine. Genome Med (2016 ) 8:60.

     Not in our library10.1186/s13073-016-0314-z

110. 110.

     Wine Y Boutz DR Lavinder JJ Miklos AE Hughes RA Hoi KH Molecular deconvolution of the monoclonal antibodies that comprise the polyclonal serum response. Proc Natl Acad Sci U S A (2013 ) 110:2993–8.

     Not in our library10.1073/pnas.1213737110

111. 111.

     Wine Y Horton AP Ippolito GC Georgiou G. Serology in the 21st century: the molecular-level analysis of the serum antibody repertoire. Curr Opin Immunol (2015 ) 35:89–97.

     Not in our library10.1016/j.coi.2015.06.009

112. 112.

     Lavinder JJ Wine Y Giesecke C Ippolito GC Horton AP Lungu OI Identification and characterization of the constituent human serum antibodies elicited by vaccination. Proc Natl Acad Sci U S A (2014 ) 111:2259–64.

     Not in our library10.1073/pnas.1317793111

113. 113.

     Iversen R Snir O Stensland M Kroll JE Steinsbø Ø Korponay-Szabó IR. Strong clonal relatedness between serum and gut IgA despite different plasma cell origins. Cell Rep (2017 ) 20:2357–67.

     Not in our library10.1016/j.celrep.2017.08.036

114. 114.

     Chen J Zheng Q Hammers CM Ellebrecht CT Mukherjee EM Tang H-Y Proteomic analysis of pemphigus autoantibodies indicates a larger, more diverse, and more dynamic repertoire than determined by B cell genetics. Cell Rep (2017 ) 18:237–47.

     Not in our library10.1016/j.celrep.2016.12.013

115. 115.

     VanDuijn MM Dekker LJ Van IJcken JWF Sillevis Smitt PAE Luider TM. Immune repertoire after immunization as seen by next-generation sequencing and proteomics. Front Immunol (2017 ) 8:1286.

     Not in our library10.3389/fimmu.2017.01286

116. 116.

     Berger CT Greiff V Mehling M Fritz S Meier MA Hoenger G Influenza vaccine response profiles are affected by vaccine preparation and preexisting immunity, but not HIV infection. Hum Vaccin Immunother (2015 ) 11:391–6.

     Not in our library10.1080/21645515.2015.1008930

117. 117.

     Wang C Liu Y Cavanagh MM Saux SL Qi Q Roskin KM B-cell repertoire responses to varicella-zoster vaccination in human identical twins. Proc Natl Acad Sci U S A (2015 ) 112:500–5.

     Not in our library10.1073/pnas.1415875112

118. 118.

     Zhu J Ofek G Yang Y Zhang B Louder MK Lu G Mining the antibodyome for HIV-1–neutralizing antibodies with next-generation sequencing and phylogenetic pairing of heavy/light chains. Proc Natl Acad Sci U S A (2013 ) 110:6470–5.

     Not in our library10.1073/pnas.1219320110

119. 119.

     Hoehn KB Fowler A Lunter G Pybus OG. The diversity and molecular evolution of B-cell receptors during infection. Mol Biol Evol (2016 ) 33:1147–57.

     Not in our library10.1093/molbev/msw015

120. 120.

     Schramm CA Sheng Z Zhang Z Mascola JR Kwong PD Shapiro L SONAR: a high-throughput pipeline for inferring antibody ontogenies from longitudinal sequencing of B cell transcripts. B Cell Biol (2016 ) 7:372

     Not in our library10.3389/fimmu.2016.00372

121. 121.
     Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data · 2013

     No notice
122. 122.

     Barak M Zuckerman NS Edelman H Unger R Mehr R IgTree©: creating immunoglobulin variable region gene lineage trees. J Immunol Methods (2008 ) 338:67–74.

     Not in our library10.1016/j.jim.2008.06.006

123. 123.

     Andrews SF Kaur K Pauli NT Huang M Huang Y Wilson PC. High preexisting serological antibody levels correlate with diversification of the influenza vaccine response. J Virol (2015 ) 89(6):3308–17.

     Not in our library10.1128/jvi.02871-14

124. 124.

     Wu X Zhang Z Schramm CA Joyce MG Do Kwon Y Zhou T Maturation and diversity of the VRC01-antibody lineage over 15 years of chronic HIV-1 infection. Cell (2015 ) 161:470–85.

     Not in our library10.1016/j.cell.2015.03.004

125. 125.

     Yang Z Rannala B. Molecular phylogenetics: principles and practice. Nat Rev Genet (2012 ) 13:303–14.

     Not in our library10.1038/nrg3186

126. 126.

     Schliep KP. Phangorn: phylogenetic analysis in R. Bioinformatics (2011 ) 27:592–3.

     Not in our library10.1093/bioinformatics/btq706

127. 127.

     Paradis E Claude J Strimmer K. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics (2004 ) 20:289–90.

     Not in our library10.1093/bioinformatics/btg412

128. 128.

     Boc A Diallo AB Makarenkov V. T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks. Nucleic Acids Res (2012 ) 40:W573–9.

     Not in our library10.1093/nar/gks485

129. 129.

     Larkin MA Blackshields G Brown NP Chenna R McGettigan PA McWilliam H Clustal W and clustal X version 2.0. Bioinformatics (2007 ) 23:2947–8.

     Not in our library10.1093/bioinformatics/btm404

130. 130.

     Swofford D Begle DP PAUP: Phylogenetic Analysis Using Parsimony, Version 3.1, March 1993. Illinois: Center for Biodiversity, Natural History Survey (1993 ).

     Not in our library

131. 131.

     Giribet G TNT: Tree analysis using New Technology. Syst Biol (2005 ) 54:176–8.

     Not in our library10.1080/10635150590905830

132. 132.

     Felsenstein J PHYLIP—Phylogeny Inference Package (version 3.2). Cladistics (1989 ) 5:164–6.

     Not in our library10.1111/j.1096-0031.1989.tb00562.x

133. 133.

     Revell LJ Chamberlain SA Rphylip: an R interface for PHYLIP. Methods Ecol Evol (2014 ) 5:976–81.

     Not in our library10.1111/2041-210x.12233

134. 134.

     Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics (2014 ) 30:1312–3.

     Not in our library10.1093/bioinformatics/btu033

135. 135.

     Guindon S Lethiec F Duroux P Gascuel O PHYML Online—a web server for fast maximum likelihood-based phylogenetic inference. Nucleic Acids Res (2005 ) 33:W557–9.

     Not in our library10.1093/nar/gki352

136. 136.

     Kumar S Stecher G Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol (2016 ) 33:1870–4.

     Not in our library10.1093/molbev/msw054

137. 137.

     Ronquist F Huelsenbeck JP MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinforma Oxf Engl (2003 ) 19:1572–4.

     Not in our library10.1093/bioinformatics/btg180

138. 138.
     BEAST 2: A Software Platform for Bayesian Evolutionary Analysis · 2014

     No notice
139. 139.

     Yermanos A Greiff V Krautler NJ Menzel U Dounas A Miho E Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim). Bioinformatics (2017 ) 33(24):3938–46.

     Not in our library10.1093/bioinformatics/btx533

140. 140.

     Vieira MC Zinder D Cobey S Selection and neutral mutations drive pervasive mutability losses in long-lived B cell lineages. bioRxiv (2017 ).

     Not in our library10.1101/163741

141. 141.

     Pinheiro A de Mera IG Alves PC Gortázar C de la Fuente J Esteves PJ. Sequencing of modern lepus VDJ genes shows that the usage of VHn genes has been retained in both oryctolagus and lepus that diverged 12 million years ago. Immunogenetics (2013 ) 65:777–84.

     Not in our library10.1007/s00251-013-0728-3

142. 142.
     Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution · 2016

     No notice
143. 143.

     Yeap L-S Hwang JK Du Z Meyers RM Meng F-L Jakubauskaitė A Sequence-intrinsic mechanisms that target AID mutational outcomes on antibody genes. Cell (2015 ) 163:1124–37.

     Not in our library10.1016/j.cell.2015.10.042

144. 144.

     Betz AG Rada C Pannell R Milstein C Neuberger MS. Passenger transgenes reveal intrinsic specificity of the antibody hypermutation mechanism: clustering, polarity, and specific hot spots. Proc Natl Acad Sci U S A (1993 ) 90:2385–8.

     Not in our library10.1073/pnas.90.6.2385

145. 145.

     Cui A Niro RD Heiden JAV Briggs AW Adams K Gilbert T A Model of somatic hypermutation targeting in mice based on high-throughput Ig sequencing data. J Immunol (2016 ) 197(9):3566–74.

     Not in our library10.4049/jimmunol.1502263

146. 146.
     Gene-Specific Substitution Profiles Describe the Types and Frequencies of Amino Acid Changes during Antibody Somatic Hypermutation · 2017

     Not checked
147. 147.

     Sheng Z Schramm CA Connors M Morris L Mascola JR Kwong PD Effects of darwinian selection and mutability on rate of broadly neutralizing antibody evolution during HIV-1 infection. PLoS Comput Biol (2016 ) 12:e1004940.

     Not in our library10.1371/journal.pcbi.1004940

148. 148.

     Hoehn KB Lunter G Pybus OG. A phylogenetic codon substitution model for antibody lineages. Genetics (2017 ) 206:417–27.

     Not in our library10.1534/genetics.116.196303

149. 149.

     DeWitt WS III Mesin L Victora GD Minin VN Matsen FA IV Using genotype abundance to improve phylogenetic inference. Q-Bio (2017 ). Available from: http://arxiv.org/abs/1708.08944

     Not in our library10.1093/molbev/msy020

150. 150.

     Lozupone C Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol (2005 ) 71:8228–35.

     Not in our library10.1128/aem.71.12.8228-8235.2005

151. 151.

     de Bourcy CFA Angel CJL Vollmers C Dekker CL Davis MM Quake SR. Phylogenetic analysis of the human antibody repertoire reveals quantitative signatures of immune senescence and aging. Proc Natl Acad Sci U S A (2017 ) 114(5):1105–10.

     Not in our library10.1073/pnas.1617959114

152. 152.

     Lewitus E Morlon H. Characterizing and comparing phylogenies from their laplacian spectrum. Syst Biol (2016 ) 65:495–507.

     Not in our library10.1093/sysbio/syv116

153. 153.

     Horns F Vollmers C Dekker CL Quake SR Signatures of selection in the human antibody repertoire: selective sweeps, competing subclones, and neutral drift. bioRxiv (2017 ).

     Not in our library10.1101/145052

154. 154.

     Emerson RO DeWitt WS Vignali M Gravley J Hu JK Osborne EJ Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire. Nat Genet (2017 ) 49:659–65.

     Not in our library10.1038/ng.3822

155. 155.

     Dash P Fiore-Gartland AJ Hertz T Wang GC Sharma S Souquette A Quantifiable predictive features define epitope-specific T cell receptor repertoires. Nature (2017 ) 547:89–93.

     Not in our library10.1038/nature22383

156. 156.

     Galson JD Trück J Fowler A Clutterbuck EA Münz M Cerundolo V Analysis of B cell repertoire dynamics following hepatitis B vaccination in humans, and enrichment of vaccine-specific antibody sequences. EBioMedicine (2015 ) 2(12):2070–9.

     Not in our library10.1016/j.ebiom.2015.11.034

157. 157.

     Chen H VennDiagram: Generate High-Resolution Venn and Euler Plots. (2016 ). Available from: https://CRAN.R-project.org/package=VennDiagram.

     Not in our library

158. 158.

     Morisita M Measuring of the dispersion of individuals and analysis of the distributional patterns. Mem Fac Sci Kyushu Univ Ser E (1959 ) 2:5–23.

     Not in our library

159. 159.

     Dziubianau M Hecht J Kuchenbecker L Sattler A Stervbo U Rödelsperger C TCR Repertoire analysis by next generation sequencing allows complex differential diagnosis of T cell–related pathology. Am J Transplant (2013 ) 13:2842–54.

     Not in our library10.1111/ajt.12431

160. 160.

     Rempala GA Seweryn M Ignatowicz L. Model for comparative analysis of antigen receptor repertoires. J Theor Biol (2011 ) 269:1–15.

     Not in our library10.1016/j.jtbi.2010.10.001

161. 161.

     Bolen CR Rubelt F Vander Heiden JA Davis MM. The repertoire dissimilarity index as a method to compare lymphocyte receptor repertoires. BMC Bioinformatics (2017 ) 18:155.

     Not in our library10.1186/s12859-017-1556-5

162. 162.

     Yokota R Kaminaga Y Kobayashi TJ. Quantification of inter-sample differences in T-cell receptor repertoires using sequence-based information. Front Immunol (2017 ) 8:1500.

     Not in our library10.3389/fimmu.2017.01500

163. 163.
     Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 · 2014

     No notice
164. 164.

     Bürckert J-P Dubois ARSX Faison WJ Farinelle S Charpentier E Sinner R Functionally convergent B cell receptor sequences in transgenic rats expressing a Human B cell repertoire in response to tetanus toxoid and measles antigens. Front Immunol (2017 ) 8:1834.

     Not in our library10.3389/fimmu.2017.01834

165. 165.

     Sun Y Best K Cinelli M Heather JM Reich-Zeliger S Shifrut E Specificity, privacy, and degeneracy in the CD4 T cell receptor repertoire following immunization. Front Immunol (2017 ) 8:430.

     Not in our library10.3389/fimmu.2017.00430

166. 166.

     Sun Cinelli M Best K Heather JM Reich-Zeliger S Shifrut E Friedman N Feature selection using a one dimensional naïve Bayes’ classifier increases the accuracy of support vector machine classification of CDR3 repertoires. Bioinformatics (2017 ) 33:951–5.

     Not in our library10.1093/bioinformatics/btw771

167. 167.

     Atchley WR Zhao J Fernandes AD Drüke T. Solving the protein sequence metric problem. Proc Natl Acad Sci U S A (2005 ) 102:6395–400.

     Not in our library10.1073/pnas.0408677102

168. 168.

     Thomas N Best K Cinelli M Reich-Zeliger S Gal H Shifrut E Tracking global changes induced in the CD4 T cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinforma Oxf Engl (2014 ) 30(22):3181–8.

     Not in our library10.1093/bioinformatics/btu523

169. 169.

     Kidera A Konishi Y Oka M Ooi T Scheraga HA Statistical analysis of the physical properties of the 20 naturally occurring amino acids. J Protein Chem (1985 ) 4:23–55.

     Not in our library10.1007/bf01025492

170. 170.
     Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning · 2019

     Not checked
171. 171.
     Statistical classifiers for diagnosing disease from immune repertoires: a case study using multiple sclerosis · 2017

     Not checked
172. 172.

     Apeltsin L Wang S Büdingen H-C Sirota M. A haystack heuristic for autoimmune disease biomarker discovery using next-gen immune repertoire sequencing data. Sci Rep (2017 ) 7:5338.

     Not in our library10.1038/s41598-017-04439-5

173. 173.

     Torkamani A Andersen KG Steinhubl SR Topol EJ. High-definition medicine. Cell (2017 ) 170:828–43.

     Not in our library10.1016/j.cell.2017.08.007

174. 174.

     Boyd SD Crowe JE Jr. Deep sequencing and human antibody repertoire analysis. Curr Opin Immunol (2016 ) 40:103–9.

     Not in our library10.1016/j.coi.2016.03.008

175. 175.

     Heather JM Ismail M Oakes T Chain B. High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities. Brief Bioinform (2017 ):bbw138.

     Not in our library10.1093/bib/bbw138

176. 176.

     Glanville J Huang H Nau A Hatton O Wagar LE Rubelt F Identifying specificity groups in the T cell receptor repertoire. Nature (2017 ) 547:94–8.

     Not in our library10.1038/nature22976

177. 177.

     Shugay M Bagaev DV Zvyagin IV Vroomans RM Crawford JC Dolton G VDJdb: a curated database of T-cell receptor sequences with known antigen specificity. Nucleic Acids Res (2018 ) 46(D1):D419–27.

     Not in our library10.1093/nar/gkx760

178. 178.

     Tickotsky N Sagiv T Prilusky J Shifrut E Friedman N. McPAS-TCR: a manually curated catalogue of pathology-associated T cell receptor sequences. Bioinformatics (2017 ) 33(18):2924–9.

     Not in our library10.1093/bioinformatics/btx286

179. 179.

     Martin ACR Protein sequence and structure analysis of antibody variable domains. In: Kontermann R Dübel S, editors. Antibody Engineering. Berlin, Heidelberg: Springer Berlin Heidelberg (2016 ). p. 33–51. Available from: http://link.springer.com/10.1007/978-3-642-01147-4_3

     Not in our library

180. 180.
     The immune epitope database (IEDB) 3.0 · 2014

     No notice
181. 181.
     Opportunities and obstacles for deep learning in biology and medicine · 2018

     No notice
182. 182.

     Jurtz VI Rosenberg Johansen A Nielsen M Armenteros A Juan J Nielsen H An introduction to deep learning on biological sequence data – examples and solutions. Bioinformatics (2017 ) 33(22):3685–90.

     Not in our library10.1093/bioinformatics/btx531

183. 183.

     Lee J Boutz DR Chromikova V Joyce MG Vollmers C Leung K Molecular-level analysis of the serum antibody repertoire in young adults before and after seasonal influenza vaccination. Nat Med (2016 ) 22:1456–64.

     Not in our library10.1038/nm.4224

184. 184.

     Snir O Chen X Gidoni M du Pré MF Zhao Y Steinsbø Ø Stereotyped antibody responses target posttranslationally modified gluten in celiac disease. JCI Insight (2017 ) 2:93961.

     Not in our library10.1172/jci.insight.93961

185. 185.

     Mamoshina P Vieira A Putin E Zhavoronkov A. Applications of deep learning in biomedicine. Mol Pharm (2016 ) 13:1445–54.

     Not in our library10.1021/acs.molpharmaceut.5b00982

186. 186.

     Greiff V Redestig H Luck J Bruni N Valai A Hartmann S A minimal model of peptide binding predicts ensemble properties of serum antibodies. BMC Genomics (2012 ) 13:79.

     Not in our library10.1186/1471-2164-13-79

187. 187.

     Becattini S Latorre D Mele F Foglierini M Gregorio CD Cassotta A Functional heterogeneity of human memory CD4+ T cell clones primed by pathogens or vaccines. Science (2014 ) 347:400–6.

     Not in our library10.1126/science.1260668

188. 188.

     Kaplinsky J Li A Sun A Coffre M Koralov SB Arnaout R. Antibody repertoire deep sequencing reveals antigen-independent selection in maturing B cells. Proc Natl Acad Sci U S A (2014 ) 111:E2622–9.

     Not in our library10.1073/pnas.1403278111

189. 189.

     Ghraichy M Galson JD Kelly DF Trück J. B-cell receptor repertoire sequencing in patients with primary immunodeficiency: a review. Immunology (2018 ) 153(2):145–60.

     Not in our library10.1111/imm.12865

190. 190.

     Khavrutskii IV Chaudhury S Stronsky SM Lee DW Benko JG Wallqvist A Quantitative analysis of repertoire-scale immunoglobulin properties in vaccine-induced B-cell responses. Front Immunol (2017 ) 8:910.

     Not in our library10.3389/fimmu.2017.00910

191. 191.

     Galson JD Trück J Clutterbuck EA Fowler A Cerundolo V Pollard AJ B-cell repertoire dynamics after sequential hepatitis B vaccination and evidence for cross-reactive B-cell activation. Genome Med (2016 ) 8:68.

     Not in our library10.1186/s13073-016-0322-z

192. 192.

     Ellebedy AH Jackson KJL Kissick HT Nakaya HI Davis CW Roskin KM Defining antigen-specific plasmablast and memory B cell subsets in human blood after viral infection or vaccination. Nat Immunol (2016 ) 17:1226–34.

     Not in our library10.1038/ni.3533

193. 193.

     Parameswaran P Liu Y Roskin KM Jackson KKL Dixit VP Lee J-Y Convergent antibody signatures in human dengue. Cell Host Microbe (2013 ) 13:691–700.

     Not in our library10.1016/j.chom.2013.05.008

194. 194.

     Shlemov A Bankevich S Bzikadze A Turchaninova MA Safonova Y Pevzner PA. Reconstructing antibody repertoires from error-prone immunosequencing reads. J Immunol (2017 ) 199(9):3369–80.

     Not in our library10.4049/jimmunol.1700485

195. 195.

     Safonova Y Lapidus A Lill J. IgSimulator: a versatile immunosequencing simulator. Bioinformatics (2015 ) 31(19):3213–5.

     Not in our library10.1093/bioinformatics/btv326

196. 196.

     Friedensohn S Khan TA Reddy ST Advanced methodologies in high-throughput sequencing of immune repertoires. Trends Biotechnol (2016 ) 35(3):203–14.

     Not in our library10.1016/j.tibtech.2016.09.010

197. 197.

     Bolotin DA Poslavsky S Mitrophanov I Shugay M Mamedov IZ Putintseva EV MiXCR: software for comprehensive adaptive immunity profiling. Nat Methods (2015 ) 12:380–1.

     Not in our library10.1038/nmeth.3364

198. 198.

     Gupta NT Adams KD Briggs AW Timberlake SC Vigneault F Kleinstein SH. Hierarchical clustering can identify B cell clones with high confidence in Ig repertoire sequencing data. J Immunol (2017 ) 198(6):2489–99.

     Not in our library10.4049/jimmunol.1601850

199. 199.

     Brown SD Raeburn LA Holt RA. Profiling tissue-resident T cell repertoires by RNA sequencing. Genome Med (2015 ) 7:125.

     Not in our library10.1186/s13073-015-0248-x

200. 200.

     Rizzetto S Koppstein DN Samir J Singh M Reed JH Cai CH B-cell receptor reconstruction from single-cell RNA-seq with VDJPuzzle. bioRxiv (2017 ):181156

     Not in our library10.1101/181156

201. 201.

     Mangul S Mandric I Yang HT Strauli N Montoya D Rotman J Profiling adaptive immune repertoires across multiple human tissues by RNA sequencing. bioRxiv (2016 ):089235

     Not in our library10.1101/089235

202. 202.

     Lindeman I Emerton G Sollid LM Teichmann S Stubbington MJT BraCeR: Reconstruction of B-cell receptor sequences and clonality inference from single-cell RNA-sequencing. bioRxiv (2017 ):185504

     Not in our library10.1101/185504

203. 203.

     Stubbington MJT Lönnberg T Proserpio V Clare S Speak AO Dougan G T cell fate and clonality inference from single-cell transcriptomes. Nat Methods (2016 ) 13:329–32.

     Not in our library10.1038/nmeth.3800

204. 204.

     Li B Li T Pignon J-C Wang B Wang J Shukla SA Landscape of tumor-infiltrating T cell repertoire of human cancers. Nat Genet (2016 ) 48:725–32.

     Not in our library10.1038/ng.3581

205. 205.

     Geering B Fussenegger M. Synthetic immunology: modulating the human immune system. Trends Biotechnol (2015 ) 33:65–79.

     Not in our library10.1016/j.tibtech.2014.10.006

206. 206.

     Roybal KT Lim WA. Synthetic immunology: hacking immune cells to expand their therapeutic capabilities. Annu Rev Immunol (2017 ) 35:229–53.

     Not in our library10.1146/annurev-immunol-051116-052302

207. 207.

     Jiang N. Immune engineering: from systems immunology to engineering immunity. Curr Opin Biomed Eng (2017 ) 1:54–62.

     Not in our library10.1016/j.cobme.2017.03.002

208. 208.

     Liu XS Mardis ER. Applications of immunogenomics to cancer. Cell (2017 ) 168:600–12.

     Not in our library10.1016/j.cell.2017.01.014

209. 209.

     Ravn U Gueneau F Baerlocher L Osteras M Desmurs M Malinge P By-passing in vitro screening—next generation sequencing technologies applied to antibody display and in silico candidate selection. Nucleic Acids Res (2010 ) 38:e193

     Not in our library10.1093/nar/gkq789

210. 210.

     Parola C Neumeier D Reddy ST. Integrating high-throughput screening and sequencing for monoclonal antibody discovery and engineering. Immunology (2018 ) 153(1):31–41.

     Not in our library10.1111/imm.12838

Cited by papers we hold 1

• Computational approaches to therapeutic antibody design: established methods and emerging trends · 2019
  No notice

Reads

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.