A computational framework to explore large-scale biosynthetic diversity

[1]  K. A. Short,et al.  The complete genomic sequence of Streptomyces spectabilis NRRL-2792 and identification of secondary metabolite biosynthetic gene clusters , 2019, Journal of Industrial Microbiology & Biotechnology.

[2]  Ajit Singh,et al.  Machine Learning With Python , 2019 .

[3]  Ryan A McClure,et al.  Discovery of the Tyrobetaine Natural Products and Their Biosynthetic Gene Cluster via Metabologenomics. , 2018, ACS chemical biology.

[4]  Elizabeth A. Shank,et al.  Large-Scale Bioinformatics Analysis of Bacillus Genomes Uncovers Conserved Roles of Natural Products in Bacterial Physiology , 2017, mSystems.

[5]  Oliver Kohlbacher,et al.  SANDPUMA: ensemble predictions of nonribosomal peptide chemistry reveal biosynthetic diversity across Actinobacteria , 2017, Bioinform..

[6]  I. Ebersberger,et al.  Natural product diversity associated with the nematode symbionts Photorhabdus and Xenorhabdus , 2017, Nature Microbiology.

[7]  Donovan H. Parks,et al.  Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life , 2017, Nature Microbiology.

[8]  William H. Gerwick,et al.  Retrospective analysis of natural products provides insights for future discovery trends , 2017, Proceedings of the National Academy of Sciences.

[9]  Michael A. Skinnider,et al.  PRISM 3: expanded prediction of natural product chemical structures from microbial genomes , 2017, Nucleic Acids Res..

[10]  Kai Blin,et al.  antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification , 2017, Nucleic Acids Res..

[11]  Kristian Fog Nielsen,et al.  Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species , 2017, Nature Microbiology.

[12]  Lena Gerwick,et al.  Comparative genomics uncovers the prolific and distinctive metabolic potential of the cyanobacterial genus Moorea , 2017, Proceedings of the National Academy of Sciences.

[13]  Vinayak Agarwal,et al.  Metagenomic discovery of polybrominated diphenyl ether biosynthesis by marine sponges , 2017, Nature chemical biology.

[14]  Chad W. Johnston,et al.  Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching. , 2016, Nature chemical biology.

[15]  Ryan A McClure,et al.  Elucidating the Rimosamide-Detoxin Natural Product Families and Their Biosynthesis Using Metabolite/Gene Cluster Correlations. , 2016, ACS chemical biology.

[16]  Ryan A McClure,et al.  New Aspercryptins, Lipopeptide Natural Products, Revealed by HDAC Inhibition in Aspergillus nidulans. , 2016, ACS chemical biology.

[17]  F. Barona-Gómez,et al.  Phylogenomic Analysis of Natural Products Biosynthetic Gene Clusters Allows Discovery of Arseno-Organic Metabolites in Model Streptomycetes , 2016, bioRxiv.

[18]  Ryan A McClure,et al.  Metabologenomics: Correlation of Microbial Gene Clusters with Metabolites Drives Discovery of a Nonribosomal Peptide with an Unusual Amino Acid Monomer , 2016, ACS central science.

[19]  Richard H. Baltz,et al.  Natural product discovery: past, present, and future , 2016, Journal of Industrial Microbiology & Biotechnology.

[20]  Hadley Wickham,et al.  An Implementation of the Grammar of Graphics , 2015 .

[21]  Michael A. Skinnider,et al.  Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM) , 2015, Nucleic acids research.

[22]  Michael A. Skinnider,et al.  An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products , 2015, Nature Communications.

[23]  Michael A Fischbach,et al.  Computational approaches to natural product discovery. , 2015, Nature chemical biology.

[24]  M. Smanski,et al.  Minimum Information about a Biosynthetic Gene cluster. , 2015, Nature chemical biology.

[25]  R. Kolter,et al.  Natural products in soil microbe interactions and evolution. , 2015, Natural product reports.

[26]  Kai Blin,et al.  antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters , 2015, Nucleic Acids Res..

[27]  Anna Lechner,et al.  Molecular networking and pattern-based genome mining improves discovery of biosynthetic gene clusters and their products from Salinispora species. , 2015, Chemistry & biology.

[28]  Paula Y. Calle,et al.  Multiplexed metagenome mining using short DNA sequence tags facilitates targeted discovery of epoxyketone proteasome inhibitors , 2015, Proceedings of the National Academy of Sciences.

[29]  Andrej Sali,et al.  A Systematic Computational Analysis of Biosynthetic Gene Cluster Evolution: Lessons for Engineering Biosynthesis , 2014, PLoS Comput. Biol..

[30]  Neil L Kelleher,et al.  A Roadmap for Natural Product Discovery Based on Large-Scale Genomics and Metabolomics , 2014, Nature chemical biology.

[31]  Rainer Breitling,et al.  Pep2Path: Automated Mass Spectrometry-Guided Genome Mining of Peptidic Natural Products , 2014, PLoS Comput. Biol..

[32]  Pavel A. Pevzner,et al.  NRPquest: Coupling Mass Spectrometry and Genome Mining for Nonribosomal Peptide Discovery , 2014, Journal of natural products.

[33]  Roger G. Linington,et al.  Insights into Secondary Metabolism from a Global Analysis of Prokaryotic Biosynthetic Gene Clusters , 2014, Cell.

[34]  Nuno Bandeira,et al.  Automated Genome Mining of Ribosomal Peptide Natural Products , 2014, ACS chemical biology.

[35]  Krystle L. Chavarria,et al.  Diversity and evolution of secondary metabolism in the marine actinomycete genus Salinispora , 2014, Proceedings of the National Academy of Sciences.

[36]  Nuno Bandeira,et al.  MS/MS networking guided analysis of molecule and gene cluster families , 2013, Proceedings of the National Academy of Sciences.

[37]  J. Davies,et al.  Specialized microbial metabolites: functions and origins , 2013, The Journal of Antibiotics.

[38]  Kai Blin,et al.  antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers , 2013, Nucleic Acids Res..

[39]  K. Katoh,et al.  MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability , 2013, Molecular biology and evolution.

[40]  Jörn Piel,et al.  Metagenome Mining Reveals Polytheonamides as Posttranslationally Modified Ribosomal Peptides , 2012, Science.

[41]  Nuno Bandeira,et al.  Mass spectral molecular networking of living microbial colonies , 2012, Proceedings of the National Academy of Sciences.

[42]  Sergey I. Nikolenko,et al.  SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing , 2012, J. Comput. Biol..

[43]  L. Holm,et al.  The Pfam protein families database , 2011, Nucleic Acids Res..

[44]  Kai Blin,et al.  antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences , 2011, Nucleic Acids Res..

[45]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[46]  Evgeny M. Zdobnov,et al.  The Newick utilities: high-throughput phylogenetic tree processing in the Unix shell , 2010, Bioinform..

[47]  Adam P. Arkin,et al.  FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix , 2009, Molecular biology and evolution.

[48]  J. Suh,et al.  The Gene Cluster for Spectinomycin Biosynthesis and the Aminoglycoside-Resistance Function of spcM in Streptomycesspectabilis , 2008, Current Microbiology.

[49]  M. Fischbach,et al.  The evolution of gene collectives: How natural selection drives chemical innovation , 2008, Proceedings of the National Academy of Sciences.

[50]  Roy D. Welch,et al.  Complete genome sequence of the myxobacterium Sorangium cellulosum , 2007, Nature Biotechnology.

[51]  Corinna Lange,et al.  Genomics-driven discovery of PKS-NRPS hybrid metabolites from Aspergillus nidulans. , 2007, Nature chemical biology.

[52]  Delbert Dueck,et al.  Clustering by Passing Messages Between Data Points , 2007, Science.

[53]  Lei Zhu,et al.  An initial strategy for comparing proteins at the domain architecture level , 2006, Bioinform..

[54]  Robert C. Edgar,et al.  MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.

[55]  Robert P. Hausinger,et al.  Fe(II)/α-Ketoglutarate-Dependent Hydroxylases and Related Enzymes , 2004 .

[56]  B. Barrell,et al.  Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2) , 2002, Nature.

[57]  Wei Qian,et al.  Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. , 2000, Molecular biology and evolution.

[58]  H. Seto,et al.  The Structures of Minor Congeners of the Detoxin Complex , 1981 .

[59]  H. Seto,et al.  The detoxin complex, selective antagonists of blasticidin S. , 1968, The Journal of antibiotics.

[60]  K. Katoh,et al.  Improvements in Performance and Usability , 2013 .

[61]  Hadley Wickham,et al.  Mastering the grammar , 2009 .

[62]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[63]  D. Holdstock Past, present--and future? , 2005, Medicine, conflict, and survival.