Bioinformatics (Zavolan)

Mittal, Nitish et al. (2024) ‘Calorie restriction and rapamycin distinctly restore non-canonical ORF translation in the muscles of aging mice’, npj Regenerative Medicine, 9(1). Available at: https://doi.org/10.1038/s41536-024-00369-9.

Leo, Simone et al. (2024) ‘Recording provenance of workflow runs with RO-Crate’, PLOS ONE, 19(9), p. e0309210. Available at: https://doi.org/10.1371/journal.pone.0309210.

Banerjee, Arka et al. (2024) ‘Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding of a subset of proteins with alpha helical domains’, Nucleic Acids Research, 52(15), pp. 9028–9048. Available at: https://doi.org/10.1093/nar/gkae630.

Ataman, Meric et al. (2024) ‘Calorie restriction and rapamycin distinctly mitigate aging-associated protein phosphorylation changes in mouse muscles’, Communications Biology, 7(1). Available at: https://doi.org/10.1038/s42003-024-06679-4.

Bak, Maciej et al. (2024) ‘MAPP unravels frequent co-regulation of splicing and polyadenylation by RNA-binding proteins and their dysregulation in cancer’, Nature Communications, 15(1). Available at: https://doi.org/10.1038/s41467-024-48046-1.

Bak, Maciej et al. (2024) ‘Supplementary Results’. Available at: https://doi.org/10.5281/zenodo.10849750.

Bak, Maciej et al. (2024) ‘MAPP’, Nature Communications, 15(1). Available at: https://doi.org/10.5281/zenodo.10845501.

Kanitz, Alexander et al. (2024) ‘The GA4GH Task Execution API: Enabling Easy Multi Cloud Task Execution’, Computing in Science and Engineering [Preprint]. Available at: https://doi.org/10.1109/MCSE.2024.3414994.

Kanitz, A. et al. (2024) ‘The GA4GH Task Execution API: Enabling Easy Multi Cloud Task Execution’, arXiv [Preprint]. Available at: https://doi.org/10.48550/arXiv.2405.00013.

Bryce-Smith, Sam et al. (2023) ‘Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data’, RNA, 29(12), pp. 1839–1855. Available at: https://doi.org/10.1261/rna.079849.123.

Kensche, Philip Reiner et al. (2023) ‘Executing workflows in the cloud with WESkit’. BioHackrXiv. Available at: https://doi.org/10.37044/osf.io/2z6nu.

Bohmann, Dirk et al. (2023) ‘Walter Keller (1938-2023): a tribute from his mentees’, RNA, 29(9), pp. v–xiii. Available at: https://doi.org/10.1261/rna.079742.123.

de Smalen, Laura M. et al. (2023) ‘Impaired age-associated mitochondrial translation is mitigated by exercise and PGC-1α’, Proceedings of the National Academy of Sciences (PNAS), 120(36), p. e2302360120. Available at: https://doi.org/10.1073/pnas.2302360120.

Katsantoni, Maria, van Nimwegen, Erik and Zavolan, Mihaela (2023) ‘Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs’, Genome Biology, 24(1), p. 77. Available at: https://doi.org/10.1186/s13059-023-02913-0.

Leo, S. et al. (2023) ‘Recording provenance of workflow runs with RO-Crate’. Available at: https://doi.org/10.48550/arXiv.2312.07852.

Moon, Youngbin, Burri, Dominik and Zavolan, Mihaela (2023) ‘Identification of experimentally-supported poly(A) sites in single-cell RNA-seq data with SCINPAS’, NAR genomics and bioinformatics, 5(3), p. lqad079. Available at: https://doi.org/10.1093/nargab/lqad079.

Seyres, Denis et al. (2023) ‘T helper cells exhibit a dynamic and reversible 3’UTR landscape’, RNA, 4(30), p. 418. Available at: https://doi.org/10.1261/rna.079897.123.

Katsantoni, Maria, van Nimwegen, Erik and Zavolan, Mihaela (2022) ‘Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs’. bioRxiv. Available at: https://doi.org/10.1101/2022.07.06.498949.

Ilaslan, Erkut et al. (2022) ‘Distinct Roles of NANOS1 and NANOS3 in the Cell Cycle and NANOS3-PUM1-FOXM1 Axis to Control G2/M Phase in a Human Primordial Germ Cell Model’, International Journal of Molecular Sciences, 23(12), p. 6592. Available at: https://doi.org/10.3390/ijms23126592.

Breda, Jeremie et al. (2022) ‘A novel approach to single cell analysis to reveal intrinsic differences in immune marker expression in unstimulated macrophages from BALB/c and C57BL/6 mouse strains’. bioRxiv. Available at: https://doi.org/10.1101/2022.05.29.493868.

Ham DJ et al. (2022) ‘Author Correction: Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle.’, 13(1). Available at: https://doi.org/10.1038/s41467-022-30189-8.

Bak, Maciej et al. (2022) ‘Frequent co-regulation of splicing and polyadenylation by RNA-binding proteins inferred with MAPP’. bioRxiv. Available at: https://doi.org/10.1101/2022.01.09.475576.

Breda, Jeremie et al. (2022) ‘A novel approach to single-cell analysis reveals intrinsic differences in immune marker expression in unstimulated BALB/c and C57BL/6 macrophages’, FEBS Letters, 596(20), pp. 2630–2643. Available at: https://doi.org/10.1002/1873-3468.14478.

Ghosh, Souvik et al. (2022) ‘CFIm-mediated alternative polyadenylation remodels cellular signaling and miRNA biogenesis’, Nucleic Acids Research, 50(6), pp. 3096–3114. Available at: https://doi.org/10.1093/nar/gkac114.

Ham, Daniel J. et al. (2022) ‘Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle’, Nature Communications, 13(1), p. 2025. Available at: https://doi.org/10.1038/s41467-022-29714-6.

Kaiser, Marco S. et al. (2022) ‘Dual roles of mTORC1-dependent activation of the ubiquitin-proteasome system in muscle proteostasis’, Communications biology, 5(1), p. 1141. Available at: https://doi.org/10.1038/s42003-022-04097-y.

Pignatti, Emanuele et al. (2022) ‘Cholesterol deprivation drives DHEA biosynthesis in human adrenals’, Endocrinology, 163(7), p. bqac076. Available at: https://doi.org/10.1210/endocr/bqac076.

Streese, Lukas et al. (2022) ‘Untargeted sequencing of circulating microRNAs in a healthy and diseased older population’, Scientific Reports, 12(1), p. 2991. Available at: https://doi.org/10.1038/s41598-022-06956-4.

Katsantoni, Maria et al. (2021) ‘ZARP: An automated workflow for processing of RNA-seq data’. bioRxiv. Available at: https://doi.org/10.1101/2021.11.18.469017.

Burri, Dominik and Zavolan, Mihaela (2021) ‘Shortening of 3’ UTRs in most cell types composing tumor tissues implicates alternative polyadenylation in protein metabolism’. bioRxiv. Available at: https://doi.org/10.1101/2021.06.30.450496.

Karousis, Evangelos D. et al. (2021) ‘Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells’. bioRxiv. Available at: https://doi.org/10.1101/2021.04.30.442116.

Mölder, Felix et al. (2021) ‘Sustainable data analysis with Snakemake’, F1000Research, 10, p. 33. Available at: https://doi.org/10.12688/f1000research.29032.1.

Börsch, Anastasiya et al. (2021) ‘Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia’, Communications Biology, 4(1), p. 194. Available at: https://doi.org/10.1038/s42003-021-01723-z.

Börsch, Anastasiya and Zavolan, Mihaela (2021) ‘Transcription factor motif activity as a biomarker of muscle aging’, American journal of aging science and research, 2(1), pp. 19–23.

Breda, Jérémie, Zavolan, Mihaela and van Nimwegen, Erik (2021) ‘Bayesian inference of gene expression states from single-cell RNA-seq data’, Nature Biotechnology, 39(8), pp. 1008–1016. Available at: https://doi.org/10.1038/s41587-021-00875-x.

Burri, Dominik and Zavolan, Mihaela (2021) ‘Shortening of 3p UTRs in most cell types composing tumor tissues implicates alternative polyadenylation in protein metabolism’, RNA (New York, N.Y.), 27(12), pp. 1459–1470. Available at: https://doi.org/10.1261/rna.078886.121.

Cléry, Antoine et al. (2021) ‘Structure of SRSF1 RRM1 bound to RNA reveals an unexpected bimodal mode of interaction and explains its involvement in SMN1 exon7 splicing’, Nature Communications, 12(1), p. 428. Available at: https://doi.org/10.1038/s41467-020-20481-w.

Coto-Llerena, Mairene et al. (2021) ‘Transcriptional Enhancer Factor Domain Family member 4 Exerts an Oncogenic Role in Hepatocellular Carcinoma by Hippo-Independent Regulation of Heat Shock Protein 70 Family Members’, Hepatology Communications, 5(4), pp. 661–674. Available at: https://doi.org/10.1002/hep4.1656.

Ghosh, Souvik et al. (2021) ‘The transcriptional landscape of a hepatoma cell line grown on scaffolds of extracellular matrix proteins’, BMC Genomics, 22(1), p. 238. Available at: https://doi.org/10.1186/s12864-021-07532-2.

Ham, Daniel J. et al. (2021) ‘Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle’. bioRxiv. Available at: https://doi.org/10.1101/2021.05.28.446097.

Karousis, Evangelos D. et al. (2021) ‘Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells’, Genome Biology, 22(1), p. 223. Available at: https://doi.org/10.1186/s13059-021-02439-3.

Mölder, Felix et al. (2021) ‘Sustainable data analysis with Snakemake’, F1000Research, 10, p. 33. Available at: https://doi.org/10.12688/f1000research.29032.2.

Rehm, Heidi L. et al. (2021) ‘GA4GH: International policies and standards for data sharing across genomic research and healthcare’, Cell Genomics, 1(2), p. 100029. Available at: https://doi.org/10.1016/j.xgen.2021.100029.

Wang, Yuluan et al. (2021) ‘MiR-CLIP reveals iso-miR selective regulation in the miR-124 targetome’, Nucleic Acids Research, 49(1), pp. 25–37. Available at: https://doi.org/10.1093/nar/gkaa1117.

Ghosh, Souvik, Börsch, Anastasiya and Zavolan, Mihaela (2020) ‘The transcriptional landscape of a hepatoma cell line grown on scaffolds of extracellular matrix proteins’. bioRxiv. Available at: https://doi.org/10.1101/2020.07.18.191395.

Ferrarini, Mariana et al. (2020) ‘Global analysis of human SARS-CoV-2 infection and host-virus interaction’. BioHackrXiv. Available at: https://doi.org/10.37044/osf.io/b4zkp.

Ghosh, Souvik et al. (2020) ‘Prevention of dsRNA-induced interferon signaling by AGO1x is linked to breast cancer cell proliferation’, The EMBO Journal, 39(18), p. e103922. Available at: https://doi.org/10.15252/embj.2019103922.

Gruber, Andreas J. and Zavolan, Mihaela (2020) ‘Reply to “A different perspective on alternative cleavage and polyadenylation”’, Nature reviews. Genetics, 21(1), pp. 63–64. Available at: https://doi.org/10.1038/s41576-019-0199-y.

Guimaraes, Joao C. et al. (2020) ‘A rare codon-based translational program of cell proliferation’, Genome Biology, 21(1), p. 44. Available at: https://doi.org/10.1186/s13059-020-1943-5.

Ham, Daniel J. et al. (2020) ‘The neuromuscular junction is a focal point of mTORC1 signaling in sarcopenia’, Nature Communications, 11(1), p. 4510. Available at: https://doi.org/10.1038/s41467-020-18140-1.

Hasler, Daniele et al. (2020) ‘The Alazami Syndrome-Associated Protein LARP7 Guides U6 Small Nuclear RNA Modification and Contributes to Splicing Robustness’, Molecular Cell, 77(5), pp. 1014–1031.e13. Available at: https://doi.org/10.1016/j.molcel.2020.01.001.

Ho-Xuan, Hung et al. (2020) ‘Gene Expression Signatures of a Preclinical Mouse Model during Colorectal Cancer Progression under Low-Dose Metronomic Chemotherapy’, Cancers, 13(1), p. 49. Available at: https://doi.org/10.3390/cancers13010049.

Iadevaia, Valentina et al. (2020) ‘Tandem RNA isolation reveals functional rearrangement of RNA-binding proteins on; CDKN1B/p27; Kip1; 3’UTRs in cisplatin treated cells’, RNA Biology, 17(1), pp. 33–46. Available at: https://doi.org/10.1080/15476286.2019.1662268.

Jutzi, Daniel et al. (2020) ‘Aberrant interaction of FUS with the U1 snRNA provides a molecular mechanism of FUS induced amyotrophic lateral sclerosis’, Nature Communications, 11(1), p. 6341. Available at: https://doi.org/10.1038/s41467-020-20191-3.

Liko, Dritan et al. (2020) ‘Loss of TSC complex enhances gluconeogenesis via upregulation of Dlk1-Dio3 locus miRNAs’, Proceedings of the National Academy of Sciences, 117(3), pp. 1524–1532. Available at: https://doi.org/10.1073/pnas.1918931117.

Breda, Jérémie, Zavolan, Mihaela and van Nimwegen, Erik (2019) ‘Bayesian inference of the gene expression states of single cells from scRNA-seq data’. bioRxiv. Available at: https://doi.org/10.1101/2019.12.28.889956.

Ghosh, Souvik et al. (2019) ‘AGO1x prevents dsRNA-induced interferon signaling to promote breast cancer cell proliferation’. bioRxiv. Available at: https://doi.org/10.1101/603506.

Gruber, Andreas J. and Zavolan, Mihaela (2019) ‘Alternative cleavage and polyadenylation in health and disease’, Nature reviews. Genetics, 20(10), pp. 599–614. Available at: https://doi.org/10.1038/s41576-019-0145-z.

Herrmann, Christina J. et al. (2019) ‘PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3′ end sequencing’, Nucleic acids research, 48(D1), pp. D174–D179. Available at: https://doi.org/10.1093/nar/gkz918.

Kanitz, Alexander et al. (2019) ‘Conserved regulation of RNA processing in somatic cell reprogramming’, BMC genomics, 20(1), p. 100. Available at: https://doi.org/10.1186/s12864-019-5438-2.

Păunescu, Virgil, Zavolan, Mihaela and Oprea, Tudor (2019) ‘In memoriam: Francisc Schneider (1933-2017)’, Journal of cellular and molecular medicine, 23(4), pp. 3045–3046. Available at: https://doi.org/10.1111/jcmm.14173.

Riba, Andrea et al. (2019) ‘Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates’, Proceedings of the National Academy of Sciences, 116(30), pp. 15023–15032. Available at: https://doi.org/10.1073/pnas.1817299116.

Sendoel, Ataman et al. (2019) ‘MINA-1 and WAGO-4 are part of regulatory network coordinating germ cell death and RNAi in C. elegans’, Cell Death & Differentiation subscription, 26(10), pp. 2157–2178. Available at: https://doi.org/10.1038/s41418-019-0291-z.

Riba, Andrea et al. (2018) ‘Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates’. bioRxiv. Available at: https://doi.org/10.1101/465914.

Essig, Katharina et al. (2018) ‘Roquin targets mRNAs in a 3′-UTR-specific manner by different modes of regulation’, Nature communications, 9(1), p. 3810. Available at: https://doi.org/10.1038/s41467-018-06184-3.

Gruber, Andreas J. et al. (2018) ‘Terminal exon characterization with TECtool reveals an abundance of cell-specific isoforms’, Nature methods, 15(10), pp. 832–836. Available at: https://doi.org/10.1038/s41592-018-0114-z.

Gruber, Andreas J. et al. (2018) ‘Discovery of physiological and cancer-related regulators of 3′ UTR processing with KAPAC’, Genome biology, 19(1), p. 44. Available at: https://doi.org/10.1186/s13059-018-1415-3.

Rzepiela, Andrzej J. et al. (2018) ‘Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction’, Molecular systems biology, 14(8), p. e8266. Available at: https://doi.org/10.15252/msb.20188266.

Zavolan, Mihaela and Gerber, André P. (2018) ‘Mirroring the multifaceted role of RNA and its partners in gene expression’, FEBS letters, 592(17), pp. 2825–2827. Available at: https://doi.org/10.1002/1873-3468.13230.

Zavolan, Mihaela and Kanitz, Alexander (2018) ‘RNA splicing and its connection with other regulatory layers in somatic cell reprogramming’, Current Opinion in Cell Biology, 52, pp. 8–13. Available at: https://doi.org/10.1016/j.ceb.2017.12.002.

Pachkov, Mikhail et al. (2017) ‘ISMARA: Completely automated inference of gene regulatory networks from high-throughput data’. PeerJ Preprints. Available at: https://doi.org/10.7287/peerj.preprints.3328v1.

Gruber, Andreas J. et al. (2017) ‘Discovery of physiological and cancer-related regulators of 3’ UTR processing with KAPAC’. bioRxiv. Available at: https://doi.org/10.1101/195958.

Dimitrova, Yoana et al. (2017) ‘TFAP2A is a component of the ZEB1/2 network that regulates TGFB1-induced epithelial to mesenchymal transition’, Biology Direct, 12(1), p. 8. Available at: https://doi.org/10.1186/s13062-017-0180-7.

Essig, Katharina et al. (2017) ‘Roquin Suppresses the PI3K-mTOR Signaling Pathway to Inhibit T Helper Cell Differentiation and Conversion of Treg to Tfr Cells’, Immunity, 47(6), pp. 1067–1082.e12. Available at: https://doi.org/10.1016/j.immuni.2017.11.008.

Gumienny, Rafal et al. (2017) ‘High-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq’, Nucleic Acids Research, 45(5), pp. 2341–2353. Available at: https://doi.org/10.1093/nar/gkw1321.

Martin, Georges et al. (2017) ‘3′ End Sequencing Library Preparation with A-seq2’, Journal of Visualized Experiments, (128), p. e56129. Available at: https://doi.org/10.3791/56129.

Mittal, Nitish et al. (2017) ‘The Gcn4 transcription factor reduces protein synthesis capacity and extends yeast lifespan’, Nature Communications, 8(457), pp. 1–12. Available at: https://doi.org/10.1038/s41467-017-00539-y.

Omidi, Saeed et al. (2017) ‘Automated incorporation of pairwise dependency in transcription factor binding site prediction using dinucleotide weight tensors’, PLoS Computational Biology, 13(7), p. e1005176. Available at: https://doi.org/10.1371/journal.pcbi.1005176.

Riba, Andrea et al. (2017) ‘Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results’, Cell Systems, 4(2), pp. 182–193. Available at: https://doi.org/10.1016/j.cels.2017.01.011.

Xu, Yanyan, Seelig, Anna and Bernèche, Simon (2017) ‘Unidirectional Transport Mechanism in an ATP Dependent Exporter’, ACS Central Science, 3(3), pp. 250–258. Available at: https://doi.org/10.1021/acscentsci.7b00068.

Zavolan, Mihaela and Graveley, Brenton R. (2017) ‘RNAs: dynamic and mutable’, Genome Biology, 18(1), p. 226. Available at: https://doi.org/10.1186/s13059-017-1361-5.

Omidi, Saeed et al. (2016) ‘Automated Incorporation of Pairwise Dependency in Transcription Factor Binding Site Prediction Using Dinucleotide Weight Tensors’. bioRxiv. Available at: https://doi.org/10.1101/078212.

Gumienny, Rafal et al. (2016) ‘High-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq.’ bioRxiv. Available at: https://doi.org/10.1101/037259.

Gruber, Andreas J. et al. (2016) ‘A comprehensive analysis of 3′ end sequencing data sets reveals novel polyadenylation signals and the repressive role of heterogeneous ribonucleoprotein C on cleavage and polyadenylation’, Genome Research, 26(8), pp. 1145–1159. Available at: https://doi.org/10.1101/gr.202432.115.

Guimaraes, Joao C. and Zavolan, Mihaela (2016) ‘Patterns of ribosomal protein expression specify normal and malignant human cells’, Genome biology, 17(1), p. 236. Available at: https://doi.org/10.1186/s13059-016-1104-z.

Janowski, Robert et al. (2016) ‘Roquin recognizes a non-canonical hexaloop structure in the 3′-UTR of Ox40’, Nature communications, 7, p. 11032. Available at: https://doi.org/10.1038/ncomms11032.

Jorjani, Hadi et al. (2016) ‘An updated human snoRNAome’, Nucleic Acids Research, 44(11), pp. 5068–5082. Available at: https://doi.org/10.1093/nar/gkw386.

Martin, Georges and Zavolan, Mihaela (2016) ‘Redesigning CLIP for efficiency, accuracy and speed’, Nature Methods, 13(6), pp. 482–3. Available at: https://doi.org/10.1038/nmeth.3870.

Swiss Institute of Bioinformatics Members, SIB and Swiss Institute of Bioinformatics Members, SIB (2016) ‘The SIB Swiss Institute of Bioinformatics” resources: focus on curated databases’, Nucleic acids research, 44(D1), pp. D27–D37. Available at: https://doi.org/10.1093/nar/gkv1310.

Ustianenko, Dmytro et al. (2016) ‘TUT-DIS3L2 is a mammalian surveillance pathway for aberrant structured non-coding RNAs’, The EMBO journal, 35(20), pp. 2179–2191. Available at: https://doi.org/10.15252/embj.201694857.

Rzepiela, Andrzej Jerzy et al. (2015) ‘Exploiting variability of single cells to uncover the in vivo hierarchy of miRNA targets’. bioRxiv. Available at: https://doi.org/10.1101/035097.

Mittal, Nitish et al. (2015) ‘Ewing sarcoma breakpoint region 1 prevents transcription-associated genome instability’. bioRxiv. Available at: https://doi.org/10.1101/034215.

Gruber, Andreas J et al. (2015) ‘A comprehensive analysis of 3′ end sequencing data sets reveals novel polyadenylation signals and the repressive role of heterogenous ribonucleoprotein C on cleavage and polyadenylation’. bioRxiv. Available at: https://doi.org/10.1101/033001.

Gumienny, Rafal and Zavolan, Mihaela (2015) ‘Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G’, Nucleic Acids Research, 43(3), pp. 1380–91. Available at: https://doi.org/10.1093/nar/gkv050.

Gumienny, Rafal and Zavolan, Mihaela (2015) ‘Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G. (erratum)’, Nucleic Acids Research, p. 9095. Available at: https://doi.org/10.1093/nar/gkv924.

Imig, Jochen et al. (2015) ‘miR-CLIP capture of a miRNA targetome uncovers a lincRNA H19-miR-106a interaction’, Nature chemical biology, 11(2), pp. 107–14. Available at: https://doi.org/10.1038/nchembio.1713.

Kanitz, Alexander et al. (2015) ‘Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data’, Genome biology, 16, p. 150. Available at: https://doi.org/10.1186/s13059-015-0702-5.

Subasic, Deni et al. (2015) ‘Cooperative target mRNA destabilization and translation inhibition by miR-58 microRNA family in C. elegans’, Genome research, 25(11), pp. 1680–91. Available at: https://doi.org/10.1101/gr.183160.114.

Tattikota, Sudhir G et al. (2015) ‘miR-184 Regulates Pancreatic β-Cell Function According to Glucose Metabolism’, Journal of biological chemistry, 290(33), pp. 20284–94. Available at: https://doi.org/10.1074/jbc.m115.658625.

Zavolan, Mihaela (2015) ‘Inferring gene expression regulatory networks from high-throughput measurements’, Methods, pp. 1–2. Available at: https://doi.org/10.1016/j.ymeth.2015.07.006.