Skip to main page content
Accesskeys
  • Page of 1
  1. Ingala M, Simmons N, Wultsch C, Krampis K, Speer K, Perkins S. Comparing Microbiome Sampling Methods in a Wild Mammal: Fecal and Intestinal Samples Record Different Signals of Host Ecology, Evolution. Frontiers in microbiology. 2018//; 9.
  2. Ali T, Kim B, Lijeron C, Dong C, Wultsch C, Krampis K. Implementation of a Reproducible, Accessible and Transparent RNA-seq Bioinformatics Pipeline within the Galaxy Platform. J Comput Sci Syst Biol. 2018//; 11(3):195-199.
  3. King C, Desai H, Sylvetsky A, LoTempio J, Ayanyan S, Carrie J, Crandall K, Fochtman B, Gasparyan L, Gulzar N, others. Baseline human gut microbiota profile in healthy people and standard reporting template. bioRxiv. 2018//; :445353.
  4. Di L, Wan Z, Akther S, Ying C, Larracuente A, Li L, Di C, Nunez R, Cucura D, Goddard N, others. Identification and quantification of Lyme pathogen strains by deep sequencing of outer surface protein C (ospC) amplicons. bioRxiv. 2018//; :332072.
  5. Alterovitz G, Dean D, Goble C, Crusoe M, Soiland-Reyes S, Bell A, Hayes A, Suresh A, King C, Taylor D, others. Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results. bioRxiv. 2018//; :191783.
  6. Dong C, Lee R, Sayad J, Krampis K. Bioinformatics Programming for Bioavailability Analysis of Sequence Patterns in Public Genomic Databases. Advancements in Bioequivalence & Bioavailability. 2018//; 1(2).
  7. Jensen TL, Frasketi M, Conway K, Villarroel L, Hill H, Krampis K, Goll JB. RSEQREP: RNA-Seq Reports, an open-source cloud-enabled framework for reproducible RNA-Seq data processing, analysis, and result reporting. F1000Res. 2017;6:2162. doi: 10.12688/f1000research.13049.2. eCollection 2017. PubMed PMID: 30026912; PubMed Central PMCID: PMC6039931.
  8. Kim B, Ali T, Lijeron C, Afgan E, Krampis K. Bio-Docklets: virtualization containers for single-step execution of NGS pipelines. Gigascience. 2017 Aug 1;6(8):1-7. doi: 10.1093/gigascience/gix048. PubMed PMID: 28854616; PubMed Central PMCID: PMC5569920.
  9. Das DK, Ali T, Krampis K, Ogunwobi OO. Fibronectin and androgen receptor expression data in prostate cancer obtained from a RNA-sequencing bioinformatics analysis. Data Brief. 2017 Apr;11:131-135. doi: 10.1016/j.dib.2017.01.016. eCollection 2017 Apr. PubMed PMID: 28210664; PubMed Central PMCID: PMC5299139.
  10. Kim B, Ali T, Krampis K, Dong C, Laungani B, Wultsch C, Lijeron C. miCloud: a plug and play, on-premises bioinformatics cloud, providing seamless integration with Illumina genome sequencers. bioRxiv. 2017//; :209734.
  11. Ali T, Kim B, Lijeron C, Ogunwobi O, Mazumder R, Krampis K. TED toolkit: a comprehensive approach for convenient transcriptomic profiling as a clinically-oriented application. PeerJ Preprints; 2017//. .
  12. Brown S, Hao Y, Chen H, Laungani B, Ali T, Dong C, Lijeron C, Kim B, Krampis K, Pei Z. Fast functional annotation of metagenomic shotgun data by DNA alignment to a microbial gene catalog. bioRxiv. 2017//; :120402.
  13. Das DK, Naidoo M, Ilboudo A, Park JY, Ali T, Krampis K, Robinson BD, Osborne JR, Ogunwobi OO. miR-1207-3p regulates the androgen receptor in prostate cancer via FNDC1/fibronectin. Exp Cell Res. 2016 Nov 1;348(2):190-200. doi: 10.1016/j.yexcr.2016.09.021. Epub 2016 Sep 29. PubMed PMID: 27693493; PubMed Central PMCID: PMC5077722.
  14. Kim B, Ali T, Hosmer S, Krampis K. Visual Omics Explorer (VOE): a cross-platform portal for interactive data visualization. Bioinformatics. 2016 Jul 1;32(13):2050-2. doi: 10.1093/bioinformatics/btw119. Epub 2016 Mar 7. PubMed PMID: 27153572; PubMed Central PMCID: PMC5860494.
  15. Bubnell J, Jamet S, Tomoiaga D, D'Hulst C, Krampis K, Feinstein P. In Vitro Mutational and Bioinformatics Analysis of the M71 Odorant Receptor and Its Superfamily. PLoS One. 2015;10(10):e0141712. doi: 10.1371/journal.pone.0141712. eCollection 2015. PubMed PMID: 26513476; PubMed Central PMCID: PMC4626375.
  16. Prince SJ, Song L, Qiu D, Maldonado Dos Santos JV, Chai C, Joshi T, Patil G, Valliyodan B, Vuong TD, Murphy M, Krampis K, Tucker DM, Biyashev R, Dorrance AE, Maroof MA, Xu D, Shannon JG, Nguyen HT. Genetic variants in root architecture-related genes in a Glycine soja accession, a potential resource to improve cultivated soybean. BMC Genomics. 2015 Feb 25;16:132. doi: 10.1186/s12864-015-1334-6. PubMed PMID: 25765991; PubMed Central PMCID: PMC4354765.
  17. Bubnell J, Jamet S, Tomoiaga D, ,,,, Krampis K, Feinstein P. In Vitro Mutational and Bioinformatics Analysis of the M71 Odorant Receptor and Its Superfamily. PloS one. 2015//; 10(10):0141712.
  18. Afgan E, Krampis K, Goonasekera N, Skala K, Taylor J. Building and provisioning bioinformatics environments on public and private Clouds. ; c2015.
  19. Prince S, Song L, Qiu D, dos Santos J, Chai C, Joshi T, Patil G, Valliyodan B, Vuong T, Murphy M, others. Genetic variants in root architecture-related genes in a Glycine soja accession, a potential resource to improve cultivated soybean. BMC genomics. 2015//; 16(1):132.
  20. Krishnakumar V, Hanlon MR, Contrino S, Ferlanti ES, Karamycheva S, Kim M, Rosen BD, Cheng CY, Moreira W, Mock SA, Stubbs J, Sullivan JM, Krampis K, Miller JR, Micklem G, Vaughn M, Town CD. Araport: the Arabidopsis information portal. Nucleic Acids Res. 2015 Jan;43(Database issue):D1003-9. doi: 10.1093/nar/gku1200. Epub 2014 Nov 20. PubMed PMID: 25414324; PubMed Central PMCID: PMC4383980.
  21. Krampis K, Wultsch C. A review of cloud computing bioinformatics solutions for next-gen sequencing data analysis and research. Methods in Next Generation Sequencing. 2015//; 2(1).
  22. Kumari P, Mazumder R, Simonyan V, Krampis K. Advantages of distributed and parallel algorithms that leverage Cloud Computing platforms for large-scale genome assembly. F1000 Research. 2015//; 4.
  23. Shamsaddini A, Pan Y, Johnson WE, Krampis K, Shcheglovitova M, Simonyan V, Zanne A, Mazumder R. Census-based rapid and accurate metagenome taxonomic profiling. BMC Genomics. 2014 Oct 21;15:918. doi: 10.1186/1471-2164-15-918. PubMed PMID: 25336203; PubMed Central PMCID: PMC4218995.
  24. Cole C, Krampis K, Karagiannis K, Almeida JS, Faison WJ, Motwani M, Wan Q, Golikov A, Pan Y, Simonyan V, Mazumder R. Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data. BMC Bioinformatics. 2014 Jan 27;15:28. doi: 10.1186/1471-2105-15-28. PubMed PMID: 24467687; PubMed Central PMCID: PMC3916084.
  25. Rusch D, Miller J, Krampis K, Tovchigrechko A, Sutton G, Yooseph S, Nelson K. Bioinformatics for Genomes and Metagenomes in Ecology Studies. Springer, Berlin, Heidelberg; 2014//. 203-226p.
  26. Goll J, Szpakowski S, Krampis K, Nelson K. Metagenomics and Microbiomes. Bioinformatics and Data Analysis in Microbiology. 2014//; :163.
  27. Nelson K, Madupu R, Szpakowski S, Goll J, Krampis K, Methe B. Next-generation sequencing, metagenomes, and the human microbiome. Nextgeneration Sequencing: Current Technologies and Applications (ed. J. Xu). Caister Academic Press. Norfolk, UK. 2014//; :141-155.
  28. Cole C, Krampis K, Karagiannis K, Almeida J, Faison W, Motwani M, Wan Q, Golikov A, Pan Y, Simonyan V, others. Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data. BMC bioinformatics. 2014//; 15(1):28.
  29. Krishnakumar V, Hanlon M, Contrino S, Ferlanti E, Karamycheva S, Kim M, Rosen B, Cheng C, Moreira W, Mock S, others. Araport: the Arabidopsis information portal. Nucleic acids research. 2014//; 43(D1):1003.
  30. Quirino B, Barreto C, Pappas G, Zengler K, Krampis K, ,,,. Genomes and Post-genome Technology. Springer, Berlin, Heidelberg; 2013//. 329-344p.
  31. Krampis K, Booth T, Chapman B, Tiwari B, Bicak M, Field D, Nelson KE. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community. BMC Bioinformatics. 2012 Mar 19;13:42. doi: 10.1186/1471-2105-13-42. PubMed PMID: 22429538; PubMed Central PMCID: PMC3372431.
  32. Wang H, Waller L, Tripathy S, St Martin S, Zhou L, Krampis K, Tucker D, Mao Y, Hoeschele I, Maroof S, others. Analysis of genes underlying soybean quantitative trait loci conferring partial resistance to Phytophthora sojae. The Plant Genome. 2010//; 3(1):23-40.
  33. Wang H, Waller L, Tripathy S, St Martin S, Zhou L, Krampis K, Tucker D, Hoeschele I, Maroof S, Tyler B, others, AMER PHYTOPATHOLOGICAL SOC 3340 PILOT KNOB ROAD SM. Discovery of genes underlying soybean QTLs conferring partial resistance to Phytophthora sojae. ; c2010.
  34. Zhou L, Mideros SX, Bao L, Hanlon R, Arredondo FD, Tripathy S, Krampis K, Jerauld A, Evans C, St Martin SK, Maroof MA, Hoeschele I, Dorrance AE, Tyler BM. Infection and genotype remodel the entire soybean transcriptome. BMC Genomics. 2009 Jan 26;10:49. doi: 10.1186/1471-2164-10-49. PubMed PMID: 19171053; PubMed Central PMCID: PMC2662884.
  35. Zhou L, Mideros S, Bao L, Hanlon R, Arredondo F, Tripathy S, Krampis K, Jerauld A, Evans C, St Martin S, others. Infection and genotype remodel the entire soybean transcriptome. BMC genomics. 2009//; 10(1):49.
  36. Krampis K. Systems View Of The Soybean Genetic Mechanisms Involved In The Response To Plant Pathogen Infection. Virginia Tech; 2009//. .
  37. Tyler B, Tripathy S, Kale S, Zhou L, Ferreira A, Dou D, Arredondo F, Mideros S, Bao L, Krampis K, others, AMER PHYTOPATHOLOGICAL SOC 3340 PILOT KNOB ROAD SM. Comparative and functional genomics of oomycete infection. ; c2009.
  38. Tyler B. Genome sequences of two Phytophthora species responsible for Sudden Oak Death and Soybean Root Rot provide novel insights into their evolutionary origins and mechanisms of pathogenesis. 2009//;
  39. Wang H, Berry S, St Martin S, Zhou L, Krampis K, Tucker D, Mao Y, Hoeschele I, Maroof M, Tyler B, others, AMER PHYTOPATHOLOGICAL SOC 3340 PILOT KNOB ROAD SM. Allele mining for genes associated with partial resistance to Phytophthora sojae in soybean. ; c2008.
  40. Tyler B, Jiang R, Zhou L, Tripathy S, Dou D, Torto-Alalibo T, Li H, Mao Y, Liu B, Vega-Sanchez M, others. Functional genomics and bioinformatics of the Phytophthora sojae soybean interaction. Springer, New York, NY; 2008//. 67-78p.
  41. Krampis K, Tyler BM, Boore JL. Extensive variation in nuclear mitochondrial DNA content between the genomes of Phytophthora sojae and Phytophthora ramorum. Mol Plant Microbe Interact. 2006 Dec;19(12):1329-36. doi: 10.1094/MPMI-19-1329. PubMed PMID: 17153917.
  42. Tyler BM, Tripathy S, Zhang X, Dehal P, Jiang RH, Aerts A, Arredondo FD, Baxter L, Bensasson D, Beynon JL, Chapman J, Damasceno CM, Dorrance AE, Dou D, Dickerman AW, Dubchak IL, Garbelotto M, Gijzen M, Gordon SG, Govers F, Grunwald NJ, Huang W, Ivors KL, Jones RW, Kamoun S, Krampis K, Lamour KH, Lee MK, McDonald WH, Medina M, Meijer HJ, Nordberg EK, Maclean DJ, Ospina-Giraldo MD, Morris PF, Phuntumart V, Putnam NH, Rash S, Rose JK, Sakihama Y, Salamov AA, Savidor A, Scheuring CF, Smith BM, Sobral BW, Terry A, Torto-Alalibo TA, Win J, Xu Z, Zhang H, Grigoriev IV, Rokhsar DS, Boore JL. Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis. Science. 2006 Sep 1;313(5791):1261-6. doi: 10.1126/science.1128796. PubMed PMID: 16946064.
  43. Tyler B, Tripathy S, Zhang X, Dehal P, Jiang R, Aerts A, Arredondo F, Baxter L, Bensasson D, Beynon J, others. Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis. Science. 2006//; 313(5791):1261-1266.
  44. Stokstad E. Genomes highlight plant pathogens? powerful arsenal. American Association for the Advancement of Science; 2006//. .
  45. Madupu R, Rogers Y, Rusch D, Miller J, Krampis K, Nelson K. Microbiomes. Reviews in Cell Biology and Molecular Medicine. 2006//;
  46. Prasinos C, Krampis K, Samakovli D, Hatzopoulos P. Tight regulation of expression of two Arabidopsis cytosolic Hsp90 genes during embryo development. J Exp Bot. 2005 Feb;56(412):633-44. doi: 10.1093/jxb/eri035. Epub 2004 Dec 6. PubMed PMID: 15582930.
  • Page of 1