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Items: 1 to 50 of 95

1.

Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences.

Mechan Llontop ME, Sharma P, Aguilera Flores M, Yang S, Pollock J, Tian L, Huang C, Rideout S, Heath LS, Li S, Vinatzer B.

Phytopathology. 2019 Dec 12. doi: 10.1094/PHYTO-09-19-0351-R. [Epub ahead of print]

PMID:
31829116
2.

NanoARG: a web service for detecting and contextualizing antimicrobial resistance genes from nanopore-derived metagenomes.

Arango-Argoty GA, Dai D, Pruden A, Vikesland P, Heath LS, Zhang L.

Microbiome. 2019 Jun 7;7(1):88. doi: 10.1186/s40168-019-0703-9.

3.

Comparing time series transcriptome data between plants using a network module finding algorithm.

Lee J, Heath LS, Grene R, Li S.

Plant Methods. 2019 Jun 1;15:61. doi: 10.1186/s13007-019-0440-x. eCollection 2019.

4.

Cyberbiosecurity Challenges of Pathogen Genome Databases.

Vinatzer BA, Heath LS, Almohri HMJ, Stulberg MJ, Lowe C, Li S.

Front Bioeng Biotechnol. 2019 May 15;7:106. doi: 10.3389/fbioe.2019.00106. eCollection 2019. Review.

5.

Effect of antibiotic use and composting on antibiotic resistance gene abundance and resistome risks of soils receiving manure-derived amendments.

Chen C, Pankow CA, Oh M, Heath LS, Zhang L, Du P, Xia K, Pruden A.

Environ Int. 2019 Jul;128:233-243. doi: 10.1016/j.envint.2019.04.043. Epub 2019 May 3.

6.

MCAT: Motif Combining and Association Tool.

Yang Y, Robertson JA, Guo Z, Martinez J, Coghlan C, Heath LS.

J Comput Biol. 2019 Jan;26(1):1-15. doi: 10.1089/cmb.2018.0113. Epub 2018 Nov 10.

PMID:
30418034
7.

MetaCompare: a computational pipeline for prioritizing environmental resistome risk.

Oh M, Pruden A, Chen C, Heath LS, Xia K, Zhang L.

FEMS Microbiol Ecol. 2018 Jul 1;94(7). doi: 10.1093/femsec/fiy079.

8.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

Arango-Argoty G, Garner E, Pruden A, Heath LS, Vikesland P, Zhang L.

Microbiome. 2018 Feb 1;6(1):23. doi: 10.1186/s40168-018-0401-z.

9.

Identification of regulatory modules in genome scale transcription regulatory networks.

Song Q, Grene R, Heath LS, Li S.

BMC Syst Biol. 2017 Dec 15;11(1):140. doi: 10.1186/s12918-017-0493-2.

10.

Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language.

Elmarakeby H, Arefiyan M, Myers E, Li S, Grene R, Heath LS.

J Comput Biol. 2017 Dec;24(12):1226-1229. doi: 10.1089/cmb.2017.0095. Epub 2017 Aug 28.

PMID:
28846457
11.

MicroTarget: MicroRNA target gene prediction approach with application to breast cancer.

Torkey H, Heath LS, ElHefnawi M.

J Bioinform Comput Biol. 2017 Aug;15(4):1750013. doi: 10.1142/S0219720017500135. Epub 2017 May 2.

PMID:
28552033
12.

Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in Arabidopsis thaliana using ChIP-Seq peak data.

Aghamirzaie D, Raja Velmurugan K, Wu S, Altarawy D, Heath LS, Grene R.

F1000Res. 2017 Mar 28;6:372. doi: 10.12688/f1000research.10041.1. eCollection 2017.

13.

PEAK: Integrating Curated and Noisy Prior Knowledge in Gene Regulatory Network Inference.

Altarawy D, Eid FE, Heath LS.

J Comput Biol. 2017 Sep;24(9):863-873. doi: 10.1089/cmb.2016.0199. Epub 2017 Mar 15.

PMID:
28294630
14.

A proposal for a portal to make earth's microbial diversity easily accessible and searchable.

Vinatzer BA, Tian L, Heath LS.

Antonie Van Leeuwenhoek. 2017 Oct;110(10):1271-1279. doi: 10.1007/s10482-017-0849-z. Epub 2017 Mar 9. Review.

PMID:
28281028
15.

A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.

Ni Y, Aghamirzaie D, Elmarakeby H, Collakova E, Li S, Grene R, Heath LS.

Front Plant Sci. 2016 Dec 23;7:1936. doi: 10.3389/fpls.2016.01936. eCollection 2016.

16.

Metagenomic profiling of historic Colorado Front Range flood impact on distribution of riverine antibiotic resistance genes.

Garner E, Wallace JS, Argoty GA, Wilkinson C, Fahrenfeld N, Heath LS, Zhang L, Arabi M, Aga DS, Pruden A.

Sci Rep. 2016 Dec 5;6:38432. doi: 10.1038/srep38432.

17.

Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data.

Badr E, ElHefnawi M, Heath LS.

PLoS One. 2016 Nov 18;11(11):e0166978. doi: 10.1371/journal.pone.0166978. eCollection 2016.

18.

MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

Arango-Argoty G, Singh G, Heath LS, Pruden A, Xiao W, Zhang L.

PLoS One. 2016 Sep 15;11(9):e0162442. doi: 10.1371/journal.pone.0162442. eCollection 2016.

20.

Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010.

Liu J, Sleeter BM, Zhu Z, Heath LS, Tan Z, Wilson TS, Sherba J, Zhou D.

Carbon Balance Manag. 2016 Jun 13;11(1):10. eCollection 2016 Dec.

21.

Potential targets of VIVIPAROUS1/ABI3-LIKE1 (VAL1) repression in developing Arabidopsis thaliana embryos.

Schneider A, Aghamirzaie D, Elmarakeby H, Poudel AN, Koo AJ, Heath LS, Grene R, Collakova E.

Plant J. 2016 Jan;85(2):305-19. doi: 10.1111/tpj.13106.

22.

DeNovo: virus-host sequence-based protein-protein interaction prediction.

Eid FE, ElHefnawi M, Heath LS.

Bioinformatics. 2016 Apr 15;32(8):1144-50. doi: 10.1093/bioinformatics/btv737. Epub 2015 Dec 16.

PMID:
26677965
23.

Transcriptome-wide functional characterization reveals novel relationships among differentially expressed transcripts in developing soybean embryos.

Aghamirzaie D, Batra D, Heath LS, Schneider A, Grene R, Collakova E.

BMC Genomics. 2015 Nov 14;16:928. doi: 10.1186/s12864-015-2108-x.

24.

CoSREM: a graph mining algorithm for the discovery of combinatorial splicing regulatory elements.

Badr E, Heath LS.

BMC Bioinformatics. 2015 Sep 4;16:285. doi: 10.1186/s12859-015-0698-6.

25.

Similarity-based codes sequentially assigned to ebolavirus genomes are informative of species membership, associated outbreaks, and transmission chains.

Weisberg AJ, Elmarakeby HA, Heath LS, Vinatzer BA.

Open Forum Infect Dis. 2015 Mar 12;2(1):ofv024. doi: 10.1093/ofid/ofv024. eCollection 2015 Jan. Erratum in: Open Forum Infect Dis. 2015 Jan;2(1):ofv041.

26.

Identifying splicing regulatory elements with de Bruijn graphs.

Badr E, Heath LS.

J Comput Biol. 2014 Dec;21(12):880-97. doi: 10.1089/cmb.2014.0183.

27.

Carbon profile of the managed forest sector in Canada in the 20th century: sink or source?

Chen J, Colombo SJ, Ter-Mikaelian MT, Heath LS.

Environ Sci Technol. 2014 Aug 19;48(16):9859-66. doi: 10.1021/es5005957. Epub 2014 Aug 11.

PMID:
25075978
28.

A system to automatically classify and name any individual genome-sequenced organism independently of current biological classification and nomenclature.

Marakeby H, Badr E, Torkey H, Song Y, Leman S, Monteil CL, Heath LS, Vinatzer BA.

PLoS One. 2014 Feb 21;9(2):e89142. doi: 10.1371/journal.pone.0089142. eCollection 2014.

29.

Evidence for extensive heterotrophic metabolism, antioxidant action, and associated regulatory events during winter hardening in Sitka spruce.

Collakova E, Klumas C, Suren H, Myers E, Heath LS, Holliday JA, Grene R.

BMC Plant Biol. 2013 Apr 30;13:72. doi: 10.1186/1471-2229-13-72.

30.

Carbon benefits from protected areas in the conterminous United States.

Zheng D, Heath LS, Ducey MJ.

Carbon Balance Manag. 2013 Apr 17;8(1):4. doi: 10.1186/1750-0680-8-4.

31.

Complete nucleotide sequences of plasmids pACK2 and pACK5 from Staphylococcus simulans biovar staphylolyticus.

Gargis AS, Heath LS, Heath HE, Leblanc PA, Gargis SR, Harris TH, Sloan GL.

Plasmid. 2013 May;69(3):257-62. doi: 10.1016/j.plasmid.2013.01.008. Epub 2013 Feb 6.

PMID:
23396145
32.

Metabolic and Transcriptional Reprogramming in Developing Soybean (Glycine max) Embryos.

Collakova E, Aghamirzaie D, Fang Y, Klumas C, Tabataba F, Kakumanu A, Myers E, Heath LS, Grene R.

Metabolites. 2013 May 14;3(2):347-72. doi: 10.3390/metabo3020347.

33.

Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos.

Aghamirzaie D, Nabiyouni M, Fang Y, Klumas C, Heath LS, Grene R, Collakova E.

Biology (Basel). 2013 Nov 21;2(4):1311-37. doi: 10.3390/biology2041311.

34.

Mining and visualization of microarray and metabolomic data reveal extensive cell wall remodeling during winter hardening in Sitka spruce (Picea sitchensis).

Grene R, Klumas C, Suren H, Yang K, Collakova E, Myers E, Heath LS, Holliday JA.

Front Plant Sci. 2012 Oct 29;3:241. doi: 10.3389/fpls.2012.00241. eCollection 2012.

35.

Mining for meaning: visualization approaches to deciphering Arabidopsis stress responses in roots and shoots.

Zhou L, Franck C, Yang K, Pilot G, Heath LS, Grene R.

OMICS. 2012 Apr;16(4):208-28. doi: 10.1089/omi.2011.0111. Epub 2012 Mar 14.

PMID:
22416883
36.

REGEN: Ancestral Genome Reconstruction for Bacteria.

Yang K, Heath LS, Setubal JC.

Genes (Basel). 2012 Jul 18;3(3):423-43. doi: 10.3390/genes3030423.

37.

ClaMS: A Classifier for Metagenomic Sequences.

Pati A, Heath LS, Kyrpides NC, Ivanova N.

Stand Genomic Sci. 2011 Nov 30;5(2):248-53. doi: 10.4056/sigs.2075298. Epub 2011 Nov 28.

38.

A synthesis of current knowledge on forests and carbon storage in the United States.

McKinley DC, Ryan MG, Birdsey RA, Giardina CP, Harmon ME, Heath LS, Houghton RA, Jackson RB, Morrison JF, Murray BC, Patakl DE, Skog KE.

Ecol Appl. 2011 Sep;21(6):1902-24.

PMID:
21939033
39.
40.

A network of SCOP hidden Markov models and its analysis.

Zhang L, Watson LT, Heath LS.

BMC Bioinformatics. 2011 May 23;12:191. doi: 10.1186/1471-2105-12-191.

41.

A theoretical model for whole genome alignment.

Belal NA, Heath LS.

J Comput Biol. 2011 May;18(5):705-28. doi: 10.1089/cmb.2010.0101. Epub 2011 Jan 6.

PMID:
21210739
42.

Complete nucleotide sequences of plasmids pACK1 and pACK3 from Staphylococcus simulans biovar staphylolyticus.

Gargis AS, Tate AH, Heath LS, Heath HE, Leblanc PA, Sloan GL.

Plasmid. 2010 Sep;64(2):104-9. doi: 10.1016/j.plasmid.2010.05.002. Epub 2010 May 21.

PMID:
20493903
43.

Greenhouse gas and carbon profile of the u.s. Forest products industry value chain.

Heath LS, Maltby V, Miner R, Skog KE, Smith JE, Unwin J, Upton B.

Environ Sci Technol. 2010 May 15;44(10):3999-4005. doi: 10.1021/es902723x.

44.

Differential expression of heat shock protein genes in preconditioning for photosynthetic acclimation in water-stressed loblolly pine.

Vásquez-Robinet C, Watkinson JI, Sioson AA, Ramakrishnan N, Heath LS, Grene R.

Plant Physiol Biochem. 2010 Apr;48(4):256-64. doi: 10.1016/j.plaphy.2009.12.005. Epub 2010 Feb 1.

PMID:
20171112
45.

Relationships between major ownerships, forest aboveground biomass distributions, and landscape dynamics in the New England region of USA.

Zheng D, Heath LS, Ducey MJ, Butler B.

Environ Manage. 2010 Feb;45(2):377-86. doi: 10.1007/s00267-009-9408-3. Epub 2009 Dec 5.

PMID:
19967361
46.

Characterization of pACK4, a mobilizable plasmid from Staphylococcus simulans biovar staphylolyticus.

Gargis AS, Heath LS, Heath HE, LeBlanc PA, Sloan GL.

Plasmid. 2009 Nov;62(3):201-5. doi: 10.1016/j.plasmid.2009.08.003. Epub 2009 Aug 26.

PMID:
19715721
47.

Zif, the zoocin A immunity factor, is a FemABX-like immunity protein with a novel mode of action.

Gargis SR, Gargis AS, Heath HE, Heath LS, LeBlanc PA, Senn MM, Berger-Bächi B, Simmonds RS, Sloan GL.

Appl Environ Microbiol. 2009 Oct;75(19):6205-10. doi: 10.1128/AEM.01011-09. Epub 2009 Aug 14.

48.

Multimodal networks: structure and operations.

Heath LS, Sioson AA.

IEEE/ACM Trans Comput Biol Bioinform. 2009 Apr-Jun;6(2):321-32. doi: 10.1109/TCBB.2007.70243.

PMID:
19407355
49.

Semantics of multimodal network models.

Heath LS, Sioson AA.

IEEE/ACM Trans Comput Biol Bioinform. 2009 Apr-Jun;6(2):271-80. doi: 10.1109/TCBB.2007.70242.

PMID:
19407351
50.

Use of 4-sulfophenyl isothiocyanate labeling and mass spectrometry to determine the site of action of the streptococcolytic peptidoglycan hydrolase zoocin A.

Gargis SR, Heath HE, Heath LS, Leblanc PA, Simmonds RS, Abbott BD, Timkovich R, Sloan GL.

Appl Environ Microbiol. 2009 Jan;75(1):72-7. doi: 10.1128/AEM.01647-08. Epub 2008 Oct 31.

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