Year |
Citation |
Score |
2023 |
Liang Z, Meng X, Schnable JC. A Transferable Machine Learning Framework for Predicting Transcriptional Responses of Genes Across Species. Methods in Molecular Biology (Clifton, N.J.). 2698: 361-379. PMID 37682485 DOI: 10.1007/978-1-0716-3354-0_21 |
0.623 |
|
2023 |
Barnes AC, Myers JL, Surber SM, Liang Z, Mower JP, Schnable JC, Roston RL. Oligogalactolipid production during cold challenge is conserved in early diverging lineages. Journal of Experimental Botany. PMID 37357909 DOI: 10.1093/jxb/erad241 |
0.529 |
|
2022 |
Liang Z, Myers ZA, Petrella D, Engelhorn J, Hartwig T, Springer NM. Mapping responsive genomic elements to heat stress in a maize diversity panel. Genome Biology. 23: 234. PMID 36345007 DOI: 10.1186/s13059-022-02807-7 |
0.327 |
|
2022 |
Read A, Weiss T, Crisp PA, Liang Z, Noshay J, Menard CC, Wang C, Song M, Hirsch CN, Springer NM, Zhang F. Genome-wide loss of CHH methylation with limited transcriptome changes in Setaria viridis domains rearranged methyltransferase (DRM) mutants. The Plant Journal : For Cell and Molecular Biology. PMID 35436373 DOI: 10.1111/tpj.15781 |
0.328 |
|
2021 |
Zhou P, Enders TA, Myers ZA, Magnusson E, Crisp PA, Noshay J, Gomez-Cano F, Liang Z, Grotewold E, Greenham K, Springer N. Prediction of conserved and variable heat and cold stress response in maize using cis-regulatory information. The Plant Cell. PMID 34735005 DOI: 10.1093/plcell/koab267 |
0.303 |
|
2021 |
Qiu Y, O'Connor CH, Della Coletta R, Renk JS, Monnahan PJ, Noshay JM, Liang Z, Gilbert A, Anderson SN, McGaugh SE, Springer NM, Hirsch CN. Whole-genome variation of transposable element insertions in a maize diversity panel. G3 (Bethesda, Md.). 11. PMID 34568911 DOI: 10.1093/g3journal/jkab238 |
0.305 |
|
2021 |
Meng X, Liang Z, Dai X, Zhang Y, Mahboub S, Ngu DW, Roston RL, Schnable JC. Predicting transcriptional responses to cold stress across plant species. Proceedings of the National Academy of Sciences of the United States of America. 118. PMID 33658387 DOI: 10.1073/pnas.2026330118 |
0.623 |
|
2020 |
Wang R, Qiu Y, Zhou Y, Liang Z, Schnable JC. A High-Throughput Phenotyping Pipeline for Image Processing and Functional Growth Curve Analysis. Plant Phenomics (Washington, D.C.). 2020: 7481687. PMID 33313562 DOI: 10.34133/2020/7481687 |
0.546 |
|
2020 |
Dai X, Xu Z, Liang Z, Tu X, Zhong S, Schnable JC, Li P. Non-homology-based prediction of gene functions in maize (Zea mays ssp. mays). The Plant Genome. 13: e20015. PMID 33016608 DOI: 10.1002/Tpg2.20015 |
0.628 |
|
2020 |
Liang Z, Qiu Y, Schnable JC. Genome-phenome wide association in maize and Arabidopsis identifies a common molecular and evolutionary signature. Molecular Plant. PMID 32171733 DOI: 10.1016/J.Molp.2020.03.003 |
0.648 |
|
2020 |
Wang R, Qiu Y, Zhou Y, Liang Z, Schnable JC. A High-Throughput Phenotyping Pipeline for Image Processing and Functional Growth Curve Analysis Plant Phenomics. 2020: 1-8. DOI: 10.34133/2020/7481687 |
0.548 |
|
2020 |
Dai X, Xu Z, Liang Z, Tu X, Zhong S, Schnable JC, Li P. Non‐homology‐based prediction of gene functions in maize (
Zea mays
ssp.
mays
) The Plant Genome. 13. DOI: 10.1002/tpg2.20015 |
0.596 |
|
2019 |
Jarquin D, Howard R, Liang Z, Gupta SK, Schnable JC, Crossa J. Enhancing Hybrid Prediction in Pearl Millet Using Genomic and/or Multi-Environment Phenotypic Information of Inbreds. Frontiers in Genetics. 10: 1294. PMID 32038702 DOI: 10.3389/Fgene.2019.01294 |
0.604 |
|
2018 |
Liang Z, Gupta SK, Yeh CT, Zhang Y, Ngu DW, Kumar R, Patil HT, Mungra KD, Yadav DV, Rathore A, Srivastava RK, Gupta R, Yang J, Varshney RK, Schnable PS, et al. Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids. G3 (Bethesda, Md.). PMID 29794163 DOI: 10.1534/G3.118.200242 |
0.585 |
|
2017 |
Liang Z, Schnable JC. Functional Divergence Between Subgenomes and Gene Pairs After Whole Genome Duplications. Molecular Plant. PMID 29275166 DOI: 10.1016/J.Molp.2017.12.010 |
0.647 |
|
2017 |
Liang Z, Pandey P, Stoerger V, Xu Y, Qiu Y, Ge Y, Schnable JC. Conventional and hyperspectral time-series imaging of maize lines widely used in field trials. Gigascience. PMID 29186425 DOI: 10.1093/Gigascience/Gix117 |
0.585 |
|
2017 |
Zhang Y, Ngu DW, Carvalho D, Liang Z, Qiu Y, Roston R, Schnable J. Differentially Regulated Orthologs in Sorghum and the Subgenomes of Maize. The Plant Cell. PMID 28733421 DOI: 10.1105/Tpc.17.00354 |
0.642 |
|
2017 |
Lai X, Behera S, Liang Z, Lu Y, Deogun JS, Schnable JC. STAG-CNS: An Order-Aware Conserved Non-coding Sequences Discovery Tool For Arbitrary Numbers of Species. Molecular Plant. PMID 28602693 DOI: 10.1016/J.Molp.2017.05.010 |
0.622 |
|
2016 |
Liang Z, Schnable JC. RNA-Seq Based Analysis of Population Structure within the Maize Inbred B73. Plos One. 11: e0157942. PMID 27348435 DOI: 10.1371/Journal.Pone.0157942 |
0.572 |
|
2016 |
Lv Y, Liang Z, Ge M, Qi W, Zhang T, Lin F, Peng Z, Zhao H. Genome-wide identification and functional prediction of nitrogen-responsive intergenic and intronic long non-coding RNAs in maize (Zea mays L.). Bmc Genomics. 17: 350. PMID 27169379 DOI: 10.1186/S12864-016-2650-1 |
0.36 |
|
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