Nicholas M. Luscombe

发表

Author Correction: A systems view of spliceosomal assembly and branchpoints with iCLIP

Michael Briese, Nejc Haberman, Christopher R. Sibley, 2020, Nature Structural & Molecular Biology.

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

Nicholas M. Luscombe, Harry Hemingway, Anoop D. Shah, 2018 .

Amino acid?base interactions: a three-dimensional analysis of protein?DNA interactions at an atomic level

Nicholas M. Luscombe, Janet M. Thornton, Roman A. Laskowski, 2001, Nucleic Acids Res..

ExpressYourself: a modular platform for processing and visualizing microarray data

Mark Gerstein, Nicholas M. Luscombe, Nathaniel Echols, 2003, Nucleic Acids Res..

GOTHiC, a simple probabilistic model to resolve complex biases and to identify real interactions in Hi-C data

Nicholas M. Luscombe, Borbala Mifsud, Inigo Martincorena, 2015, bioRxiv.

Generative adversarial networks simulate gene expression and predict perturbations in single cells

Nicholas M. Luscombe, Fiona M. Watt, Arsham Ghahramani, 2018, bioRxiv.

Generative adversarial networks simulate gene expression and predict perturbations in single cells

Nicholas M. Luscombe, Fiona M. Watt, Arsham Ghahramani, 2018, bioRxiv.

Transcription regulation: a genomic network

Nicholas M. Luscombe, N. Luscombe, 2005, BMC Bioinformatics.

Prediction of regulatory networks: genome-wide identification of transcription factor targets from gene expression data

Mark Gerstein, Jiang Qian, Nicholas M. Luscombe, 2003, Bioinform..

A pipeline for ChIP-seq data analysis (Prot 56)

Nicholas M. Luscombe, Juan M. Vaquerizas, Ruhi M. Ali, 2012 .

RNA modifications detection by comparative Nanopore direct RNA sequencing

Anton J. Enright, Nicholas M. Luscombe, Jernej Ule, 2019, Nature Communications.

Data Science Issues in Understanding Protein-RNA Interactions

Nejc Haberman, Anob M. Chakrabarti, Nicholas M. Luscombe, 2017, bioRxiv.

iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution

Blaz Zupan, Nicholas M. Luscombe, Jernej Ule, 2011, Journal of visualized experiments : JoVE.

Complete Genome Sequence of Uropathogenic Proteus mirabilis, a Master of both Adherence and Motility

Nicholas M. Luscombe, Julian Parkhill, Michael A. Quail, 2008, Journal of bacteriology.

Genomic analysis of DNA binding and gene regulation by homologous nucleoid-associated proteins IHF and HU in Escherichia coli K12

Nicholas M. Luscombe, Ruhi M. Ali, N. Luscombe, 2011, Nucleic acids research.

Direct and indirect effects of H-NS and Fis on global gene expression control in Escherichia coli

Nicholas M. Luscombe, Vladimir Benes, Sabine Schmidt, 2010, Nucleic acids research.

Genome-wide Analysis Reveals MOF as a Key Regulator of Dosage Compensation and Gene Expression in Drosophila

Nicholas M. Luscombe, Juan M. Vaquerizas, Paul Bertone, 2008, Cell.

Analytical Evolutionary Model for Protein Fold Occurrence in Genomes, Accounting for the Effects of Gene Duplication, Deletion, Acquisition and Selective Pressure

Mark Gerstein, Nicholas M. Luscombe, M. Gerstein, 2006 .

Target-Specific Precision of CRISPR-Mediated Genome Editing

Anob M. Chakrabarti, Nicholas M. Luscombe, N. Luscombe, 2018, bioRxiv.

Protein–RNA interactions: new genomic technologies and perspectives

Julian König, Nicholas M. Luscombe, Jernej Ule, 2012, Nature Reviews Genetics.

Evidence of non-random mutation rates suggests an evolutionary risk management strategy

Nicholas M. Luscombe, Iñigo Martincorena, N. Luscombe, 2012, Nature.

explains transcriptional activity in yeast A genomic model of condition-specific nucleosome behavior

Nicholas M. Luscombe, Judith B. Zaugg, N. Luscombe, 2012 .

Direct Competition between hnRNP C and U2AF65 Protects the Transcriptome from the Exonization of Alu Elements

Julian König, Nicholas M. Luscombe, Jernej Ule, 2013, Cell.

iCLIP Predicts the Dual Splicing Effects of TIA-RNA Interactions

Michael Briese, Nicholas M. Luscombe, Tomaž Curk, 2010, PLoS biology.

Identifying the genetic basis of variation in cell behaviour in human iPS cell lines from healthy donors

Nicholas M. Luscombe, Anna Laddach, Franca Fraternali, 2018, bioRxiv.

Data Science Issues in Studying Protein-RNA Interactions with CLIP Technologies.

Nejc Haberman, Anob M. Chakrabarti, Nicholas M. Luscombe, 2018, Annual review of biomedical data science.

RADICL-seq identifies general and cell type–specific principles of genome-wide RNA-chromatin interactions

Mathieu Blanchette, Nicholas M. Luscombe, Boris Lenhard, 2020, Nature Communications.