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1. Yanai, I. & Lercher, M. J. Make science disruptive again. Nat Biotechnol 41, 450–451 (2023).

2. Kroll, A., Ranjan, S., Engqvist, M. K. M. & Lercher, M. J. A general model to predict small molecule substrates of enzymes based on machine and deep learning. Nat Commun 14, 2787 (2023).

3. Balparda, M. et al. Viridiplantae-specific GLXI and GLXII isoforms co-evolved and detoxify glucosone in planta. Plant Physiol 191, 1214–1233 (2023).

4. Yanai, I. & Lercher, M. J. What puzzle are you in? Genome Biol 23, 179 (2022).

5. Yanai, I. & Lercher, M. Improvisational science. Genome Biol 23, 4 (2022).

6. Angermayr, S. A. et al. Growth-mediated negative feedback shapes quantitative antibiotic response. Mol Syst Biol 18, e10490 (2022).

7. Yanai, I. & Lercher, M. J. Iterations of evolutionA (Very) Short History of Life on Earth Henry Gee St. Martin’s Press, 2021. 288 pp. Science 374, 828 (2021).

8. Yanai, I. & Lercher, M. The data-hypothesis conversation. Genome Biol 22, 58 (2021).

9. Yanai, I. & Lercher, M. Novel predictions arise from contradictions. Genome Biol 22, 153 (2021).

10. Sundermann, E. M., Lercher, M. J. & Heckmann, D. Modeling photosynthetic resource allocation connects physiology with evolutionary environments. Sci Rep 11, 15979 (2021).

11. Moe-Lange, J. et al. Interdependence of a mechanosensitive anion channel and glutamate receptors in distal wound signaling. Sci Adv 7, eabg4298 (2021).

12. Kroll, A., Engqvist, M. K. M., Heckmann, D. & Lercher, M. J. Deep learning allows genome-scale prediction of Michaelis constants from structural features. PLoS Biol 19, e3001402 (2021).

13. Kim, J.-Y. et al. Distinct identities of leaf phloem cells revealed by single cell transcriptomics. Plant Cell 33, 511–530 (2021).

14. Kim, J.-Y. et al. Cellular export of sugars and amino acids: role in feeding other cells and organisms. Plant Physiol 187, 1893–1914 (2021).

15. Hu, X.-P. & Lercher, M. J. An optimal growth law for RNA composition and its partial implementation through ribosomal and tRNA gene locations in bacterial genomes. PLoS Genet 17, e1009939 (2021).

16. Dourado, H., Mori, M., Hwa, T. & Lercher, M. J. On the optimality of the enzyme-substrate relationship in bacteria. PLoS Biol 19, e3001416 (2021).

17. Yanai, I. & Lercher, M. The two languages of science. Genome Biol 21, 147 (2020).

18. Yanai, I. & Lercher, M. Renaissance minds in 21st century science. Genome Biol 21, 67 (2020).

19. Yanai, I. & Lercher, M. A hypothesis is a liability. Genome Biol 21, 231 (2020).

20. Singh, D. & Lercher, M. J. Network reduction methods for genome-scale metabolic models. Cell Mol Life Sci 77, 481–488 (2020).

21. Hu, X.-P., Dourado, H., Schubert, P. & Lercher, M. J. The protein translation machinery is expressed for maximal efficiency in Escherichia coli. Nat Commun 11, 5260 (2020).

22. Dourado, H. & Lercher, M. J. An analytical theory of balanced cellular growth. Nat Commun 11, 1226 (2020).

23. Yanai, I. & Lercher, M. What is the question? Genome Biol 20, 289 (2019).

24. Yanai, I. & Lercher, M. Night science. Genome Biol 20, 179 (2019).

25. Subramanian, B., Gao, S., Lercher, M. J., Hu, S. & Chen, W.-H. Evolview v3: a webserver for visualization, annotation, and management of phylogenetic trees. Nucleic Acids Res 47, W270–W275 (2019).

26. Pang, T. Y. & Lercher, M. J. Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment. Proc Natl Acad Sci U S A 116, 187–192 (2019).

27. Gao, N. L., Chen, J., Wang, T., Lercher, M. J. & Chen, W.-H. Prokaryotic Genome Expansion Is Facilitated by Phages and Plasmids but Impaired by CRISPR. Front Microbiol 10, 2254 (2019).

28. Alzoubi, D., Desouki, A. A. & Lercher, M. J. Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast. Sci Rep 9, 11837 (2019).

29. Alvarez, C. E. et al. Molecular adaptations of NADP-malic enzyme for its function in C(4) photosynthesis in grasses. Nat Plants 5, 755–765 (2019).

30. Pfeifer, B. & Lercher, M. J. BlockFeST: Bayesian calculation of region-specific FST to detect local adaptation. Bioinformatics 34, 3205–3207 (2018).

31. Heckmann, D. et al. Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models. Nat Commun 9, 5252 (2018).

32. Gao, N. L. et al. MVP: a microbe-phage interaction database. Nucleic Acids Res 46, D700–D707 (2018).

33. Denton, A. K. et al. Corrigendum: Freeze-quenched maize mesophyll and bundle sheath separation uncovers bias in previous tissue-specific RNA-Seq data. J Exp Bot 69, 3789 (2018).

34. Alzoubi, D., Desouki, A. A. & Lercher, M. J. Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations. Sci Rep 8, 17252 (2018).

35. Schmitz, J. et al. The ancestors of diatoms evolved a unique mitochondrial dehydrogenase to oxidize photorespiratory glycolate. Photosynth Res 132, 183–196 (2017).

36. Pang, T. Y. & Lercher, M. J. Supra-operonic clusters of functionally related genes (SOCs) are a source of horizontal gene co-transfers. Sci Rep 7, 40294 (2017).

37. Li, Y., Heckmann, D., Lercher, M. J. & Maurino, V. G. Combining genetic and evolutionary engineering to establish C4 metabolism in C3 plants. J Exp Bot 68, 117–125 (2017).

38. Jin, H. et al. HOTAIR rs7958904 polymorphism is associated with increased cervical cancer risk in a Chinese population. Sci Rep 7, 3144 (2017).

39. Gao, N., Lu, G., Lercher, M. J. & Chen, W.-H. Selection for energy efficiency drives strand-biased gene distribution in prokaryotes. Sci Rep 7, 10572 (2017).

40. Fritzemeier, C. J., Hartleb, D., Szappanos, B., Papp, B. & Lercher, M. J. Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal. PLoS Comput Biol 13, e1005494 (2017).

41. Denton, A. K. et al. Freeze-quenched maize mesophyll and bundle sheath separation uncovers bias in previous tissue-specific RNA-Seq data. J Exp Bot 68, 147–160 (2017).

42. Yanai, I. & Lercher, M. J. Forty years of The Selfish Gene are not enough. Genome Biol 17, 39 (2016).

43. Szappanos, B. et al. Adaptive evolution of complex innovations through stepwise metabolic niche expansion. Nat Commun 7, 11607 (2016).

44. He, Z. et al. Evolview v2: an online visualization and management tool for customized and annotated phylogenetic trees. Nucleic Acids Res 44, W236-241 (2016).

45. Hartleb, D., Jarre, F. & Lercher, M. J. Improved Metabolic Models for E. coli and Mycoplasma genitalium from GlobalFit, an Algorithm That Simultaneously Matches Growth and Non-Growth Data Sets. PLoS Comput Biol 12, e1005036 (2016).

46. Chen, W.-H., Lu, G., Bork, P., Hu, S. & Lercher, M. J. Energy efficiency trade-offs drive nucleotide usage in transcribed regions. Nat Commun 7, 11334 (2016).

47. Wittelsbürger, U., Pfeifer, B. & Lercher, M. J. WhopGenome: high-speed access to whole-genome variation and sequence data in R. Bioinformatics 31, 413–415 (2015).

48. Dilthey, A. & Lercher, M. J. Horizontally transferred genes cluster spatially and metabolically. Biol Direct 10, 72 (2015).

49. Desouki, A. A., Jarre, F., Gelius-Dietrich, G. & Lercher, M. J. CycleFreeFlux: efficient removal of thermodynamically infeasible loops from flux distributions. Bioinformatics 31, 2159–2165 (2015).

50. Schönknecht, G., Weber, A. P. M. & Lercher, M. J. Horizontal gene acquisitions by eukaryotes as drivers of adaptive evolution. Bioessays 36, 9–20 (2014).

51. Pfeifer, B., Wittelsbürger, U., Ramos-Onsins, S. E. & Lercher, M. J. PopGenome: an efficient Swiss army knife for population genomic analyses in R. Mol Biol Evol 31, 1929–1936 (2014).

52. Mallmann, J. et al. The role of photorespiration during the evolution of C4 photosynthesis in the genus Flaveria. Elife 3, e02478 (2014).

53. Esser, C., Kuhn, A., Groth, G., Lercher, M. J. & Maurino, V. G. Plant and animal glycolate oxidases have a common eukaryotic ancestor and convergently duplicated to evolve long-chain 2-hydroxy acid oxidases. Mol Biol Evol 31, 1089–1101 (2014).

54. Engqvist, M. K. M., Eßer, C., Maier, A., Lercher, M. J. & Maurino, V. G. Mitochondrial 2-hydroxyglutarate metabolism. Mitochondrion 19 Pt B, 275–281 (2014).

55. Schönknecht, G. et al. Gene transfer from bacteria and archaea facilitated evolution of an extremophilic eukaryote. Science 339, 1207–1210 (2013).

56. Heckmann, D. et al. Predicting C4 photosynthesis evolution: modular, individually adaptive steps on a Mount Fuji fitness landscape. Cell 153, 1579–1588 (2013).

57. Gelius-Dietrich, G., Desouki, A. A., Fritzemeier, C. J. & Lercher, M. J. Sybil--efficient constraint-based modelling in R. BMC Syst Biol 7, 125 (2013).

58. Zhang, H., Gao, S., Lercher, M. J., Hu, S. & Chen, W.-H. EvolView, an online tool for visualizing, annotating and managing phylogenetic trees. Nucleic Acids Res 40, W569-572 (2012).

59. Laubach, T., von Haeseler, A. & Lercher, M. J. TreeSnatcher plus: capturing phylogenetic trees from images. BMC Bioinformatics 13, 110 (2012).

60. Grassi, L., Caselle, M., Lercher, M. J. & Lagomarsino, M. C. Horizontal gene transfers as metagenomic gene duplications. Mol Biosyst 8, 790–795 (2012).

61. Chen, W.-H., Trachana, K., Lercher, M. J. & Bork, P. Younger genes are less likely to be essential than older genes, and duplicates are less likely to be essential than singletons of the same age. Mol Biol Evol 29, 1703–1706 (2012).

62. Chen, W.-H., Minguez, P., Lercher, M. J. & Bork, P. OGEE: an online gene essentiality database. Nucleic Acids Res 40, D901-906 (2012).

63. Wang, G.-Z., Liu, J., Wang, W., Zhang, H.-Y. & Lercher, M. J. A gene’s ability to buffer variation is predicted by its fitness contribution and genetic interactions. PLoS One 6, e17650 (2011).

64. Wang, G.-Z., Lercher, M. J. & Hurst, L. D. Transcriptional coupling of neighboring genes and gene expression noise: evidence that gene orientation and noncoding transcripts are modulators of noise. Genome Biol Evol 3, 320–331 (2011).

65. Wang, G.-Z. & Lercher, M. J. The effects of network neighbours on protein evolution. PLoS One 6, e18288 (2011).

66. Wang, G.-Z., Chen, W.-H. & Lercher, M. J. Coexpression of linked gene pairs persists long after their separation. Genome Biol Evol 3, 565–570 (2011).

67. Szappanos, B. et al. An integrated approach to characterize genetic interaction networks in yeast metabolism. Nat Genet 43, 656–662 (2011).

68. Chen, W.-H., Wei, W. & Lercher, M. J. Minimal regulatory spaces in yeast genomes. BMC Genomics 12, 320 (2011).

69. Bräutigam, A. et al. An mRNA blueprint for C4 photosynthesis derived from comparative transcriptomics of closely related C3 and C4 species. Plant Physiol 155, 142–156 (2011).

70. Weiss, M., Schrimpf, S., Hengartner, M. O., Lercher, M. J. & von Mering, C. Shotgun proteomics data from multiple organisms reveals remarkable quantitative conservation of the eukaryotic core proteome. Proteomics 10, 1297–1306 (2010).

71. Wang, G.-Z. & Lercher, M. J. Amino acid composition in endothermic vertebrates is biased in the same direction as in thermophilic prokaryotes. BMC Evol Biol 10, 263 (2010).

72. He, F. et al. Assessing the influence of adjacent gene orientation on the evolution of gene upstream regions in Arabidopsis thaliana. Genetics 185, 695–701 (2010).

73. Hao, L. et al. Human functional genetic studies are biased against the medically most relevant primate-specific genes. BMC Evol Biol 10, 316 (2010).

74. Chen, W.-H., de Meaux, J. & Lercher, M. J. Co-expression of neighbouring genes in Arabidopsis: separating chromatin effects from direct interactions. BMC Genomics 11, 178 (2010).

75. Warnecke, T., Wang, G.-Z., Lercher, M. J. & Hurst, L. D. Does negative auto-regulation increase gene duplicability? BMC Evol Biol 9, 193 (2009).

76. Schrimpf, S. P. et al. Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes. PLoS Biol 7, e48 (2009).

77. Chen, W.-H. & Lercher, M. J. ColorTree: a batch customization tool for phylogenic trees. BMC Res Notes 2, 155 (2009).

78. Lercher, M. J. & Pál, C. Integration of horizontally transferred genes into regulatory interaction networks takes many million years. Mol Biol Evol 25, 559–567 (2008).

79. Raes, J., Korbel, J. O., Lercher, M. J., von Mering, C. & Bork, P. Prediction of effective genome size in metagenomic samples. Genome Biol 8, R10 (2007).

80. Yanai, I. et al. Similar gene expression profiles do not imply similar tissue functions. Trends Genet 22, 132–138 (2006).

81. Savard, J. et al. Phylogenomic analysis reveals bees and wasps (Hymenoptera) at the base of the radiation of Holometabolous insects. Genome Res 16, 1334–1338 (2006).

82. Savard, J., Tautz, D. & Lercher, M. J. Genome-wide acceleration of protein evolution in flies (Diptera). BMC Evol Biol 6, 7 (2006).

83. Pál, C. et al. Chance and necessity in the evolution of minimal metabolic networks. Nature 440, 667–670 (2006).

84. Pál, C., Papp, B. & Lercher, M. J. An integrated view of protein evolution. Nat Rev Genet 7, 337–348 (2006).

85. Lercher, M. J. & Hurst, L. D. Co-expressed yeast genes cluster over a long range but are not regularly spaced. J Mol Biol 359, 825–831 (2006).

86. Legube, G., McWeeney, S. K., Lercher, M. J. & Akhtar, A. X-chromosome-wide profiling of MSL-1 distribution and dosage compensation in Drosophila. Genes Dev 20, 871–883 (2006).

87. Keightley, P. D., Lercher, M. J. & Eyre-Walker, A. Understanding the degradation of hominid gene control. PLoS Comput Biol 2, e19; author reply e26 (2006).

88. Pál, C., Papp, B. & Lercher, M. J. Horizontal gene transfer depends on gene content of the host. Bioinformatics 21 Suppl 2, ii222-223 (2005).

89. Pál, C., Papp, B. & Lercher, M. J. Adaptive evolution of bacterial metabolic networks by horizontal gene transfer. Nat Genet 37, 1372–1375 (2005).

90. Keightley, P. D., Lercher, M. J. & Eyre-Walker, A. Evidence for widespread degradation of gene control regions in hominid genomes. PLoS Biol 3, e42 (2005).

91. Hurst, L. D. & Lercher, M. J. Unusual linkage patterns of ligands and their cognate receptors indicate a novel reason for non-random gene order in the human genome. BMC Evol Biol 5, 62 (2005).

92. Webster, M. T., Smith, N. G. C., Lercher, M. J. & Ellegren, H. Gene expression, synteny, and local similarity in human noncoding mutation rates. Mol Biol Evol 21, 1820–1830 (2004).

93. Lercher, M. J., Chamary, J.-V. & Hurst, L. D. Genomic regionality in rates of evolution is not explained by clustering of genes of comparable expression profile. Genome Res 14, 1002–1013 (2004).

94. Hurst, L. D., Pál, C. & Lercher, M. J. The evolutionary dynamics of eukaryotic gene order. Nat Rev Genet 5, 299–310 (2004).

95. Lercher, M. J., Urrutia, A. O., Pavlícek, A. & Hurst, L. D. A unification of mosaic structures in the human genome. Hum Mol Genet 12, 2411–2415 (2003).

96. Lercher, M. J., Urrutia, A. O. & Hurst, L. D. Evidence that the human X chromosome is enriched for male-specific but not female-specific genes. Mol Biol Evol 20, 1113–1116 (2003).

97. Lercher, M. J. & Hurst, L. D. Imprinted chromosomal regions of the human genome have unusually high recombination rates. Genetics 165, 1629–1632 (2003).

98. Lercher, M. J., Blumenthal, T. & Hurst, L. D. Coexpression of neighboring genes in Caenorhabditis elegans is mostly due to operons and duplicate genes. Genome Res 13, 238–243 (2003).

99. Smith, N. G. C. & Lercher, M. J. Regional similarities in polymorphism in the human genome extend over many megabases. Trends Genet 18, 281–283 (2002).

100. Lercher, M. J., Urrutia, A. O. & Hurst, L. D. Clustering of housekeeping genes provides a unified model of gene order in the human genome. Nat Genet 31, 180–183 (2002).

101. Lercher, M. J., Smith, N. G. C., Eyre-Walker, A. & Hurst, L. D. The evolution of isochores: evidence from SNP frequency distributions. Genetics 162, 1805–1810 (2002).

102. Lercher, M. J. & Hurst, L. D. Human SNP variability and mutation rate are higher in regions of high recombination. Trends Genet 18, 337–340 (2002).

103. Lercher, M. J. & Hurst, L. D. Can mutation or fixation biases explain the allele frequency distribution of human single nucleotide polymorphisms (SNPs)? Gene 300, 53–58 (2002).

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