High Impact Research

Over the years, IGBB scientists have gained a reputation for publishing papers that are widely cited. Below are papers that are (a) authored/co-authored by an IGBB employee, faculty fellow, or affiliate and (b) fall within the top ten percent of scientific publications with regard to citation impact. Citation benchmarking values are from Scopus. Papers in the 99th percentile are in the top 1% globally. Citation benchmarking takes into account the date of publication, the document type, and discipline-specific factors. For a particular IGBB fellow/affiliate/staff member, only those papers published while at MS State are included. The list below is updated periodically.

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Avian-origin H3N2 canine influenza A viruses in Southern China

IGBB Authors:
Xiufeng "Henry" Wan

PUBLICATION YEAR: 2010
IMPACT FACTOR: 3.137
SCOPUS CITATIONS: 157

Indications that live poultry markets are a major source of human H5N1 influenza virus infection in China

IGBB Authors:
Xiufeng "Henry" Wan

PUBLICATION YEAR: 2011
IMPACT FACTOR: 5.432
SCOPUS CITATIONS: 139

Sequencing three crocodilian genomes to illuminate the evolution of archosaurs and amniotes

IGBB Authors:
Shane C. Burgess, Amanda M. Cooksey, Federico G. Hoffmann, Fiona M. McCarthy, Daniel G. Peterson, David A. Ray

PUBLICATION YEAR: 2012
IMPACT FACTOR: 8.448
SCOPUS CITATIONS: 115

A molecular clock for malaria parasites

IGBB Authors:
Diana C. Outlaw

PUBLICATION YEAR: 2010
IMPACT FACTOR: 18.278
SCOPUS CITATIONS: 123

On the Age of Eukaryotes: Evaluating Evidence from Fossils and Molecular Clocks

IGBB Authors:
Matthew W. Brown

PUBLICATION YEAR: 2014
IMPACT FACTOR: 7.291
SCOPUS CITATIONS: 212

Melatonin increases cleavage rate of porcine preimplantation embryos in vitro

IGBB Authors:
Erdogan Memili, Nelida Rodriguez-Osorio

PUBLICATION YEAR: 2007
IMPACT FACTOR: 4.743
SCOPUS CITATIONS: 125

A computational framework for influenza antigenic cartography

IGBB Authors:
Xiufeng "Henry" Wan

PUBLICATION YEAR: 2010
IMPACT FACTOR: 5.287
SCOPUS CITATIONS: 127

Cai Z, Zhang T, Wan XF (2010) A computational framework for influenza antigenic cartography. PLoS Computational Biology 6(10): e1000949.

DOI: 10.1371/journal.pcbi.1000949
EID: 2-s2.0-78349263426
PMID: 20949097

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ABSTRACT
Influenza viruses have been responsible for large losses of lives around the world and continue to present a great public health challenge. Antigenic characterization based on hemagglutination inhibition (HI) assay is one of the routine procedures for influenza vaccine strain selection. However, HI assay is only a crude experiment reflecting the antigenic correlations among testing antigens (viruses) and reference antisera (antibodies). Moreover, antigenic characterization is usually based on more than one HI dataset. The combination of multiple datasets results in an incomplete HI matrix with many unobserved entries. This paper proposes a new computational framework for constructing an influenza antigenic cartography from this incomplete matrix, which we refer to as Matrix Completion-Multidimensional Scaling (MC-MDS). In this approach, we first reconstruct the HI matrices with viruses and antibodies using low-rank matrix completion, and then generate the two-dimensional antigenic cartography using multidimensional scaling. Moreover, for influenza HI tables with herd immunity effect (such as those from Human influenza viruses), we propose a temporal model to reduce the inherent temporal bias of HI tables caused by herd immunity. By applying our method in HI datasets containing H3N2 influenza A viruses isolated from 1968 to 2003, we identified eleven clusters of antigenic variants, representing all major antigenic drift events in these 36 years. Our results showed that both the completed HI matrix and the antigenic cartography obtained via MC-MDS are useful in identifying influenza antigenic variants and thus can be used to facilitate influenza vaccine strain selection. The webserver is available at http://sysbio.cvm.msstate.edu/AntigenMap.

Bacterial diversity analysis of huanglongbing pathogen-infected citrus, using phyloChip arrays and 16S rRNA gene clone library sequencing

IGBB Authors:
Shien Lu, Nian Wang

PUBLICATION YEAR: 2009
IMPACT FACTOR: 4.057
SCOPUS CITATIONS: 129

Structure and evolution of cereal genomes

IGBB Authors:
Daniel G. Peterson

PUBLICATION YEAR: 2003
IMPACT FACTOR: 11.589
SCOPUS CITATIONS: 84

HPIDB - a unified resource for host-pathogen interactions

IGBB Authors:
Bindu Nanduri, Ranjit S. Kumar

PUBLICATION YEAR: 2010
IMPACT FACTOR: 3.765
SCOPUS CITATIONS:

Functional genomics of the chicken--a model organism

IGBB Authors:
Shane C. Burgess

PUBLICATION YEAR: 2007
IMPACT FACTOR: 1.801
SCOPUS CITATIONS: 102

Cogburn LA, Porter TE, Duclos MJ, Simon J, Burgess SC, Zhu JJ, Cheng HH, Dodgson JB, Burnside J (2007) Functional genomics of the chicken--a model organism. Poultry Science 86(10): 2059-2094.

DOI: 10.1093/ps/86.10.2059
EID: 2-s2.0-35348826030
PMID: 17878436

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ABSTRACT
Since the sequencing of the genome and the development of high-throughput tools for the exploration of functional elements of the genome, the chicken has reached model organism status. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scale. Systems biology attempts to integrate functional information derived from multiple high-content data sets into a holistic view of all biological processes within a cell or organism. Generation of a large collection ( approximately 600K) of chicken expressed sequence tags, representing most tissues and developmental stages, has enabled the construction of high-density microarrays for transcriptional profiling. Comprehensive analysis of this large expressed sequence tag collection and a set of approximately 20K full-length cDNA sequences indicate that the transcriptome of the chicken represents approximately 20,000 genes. Furthermore, comparative analyses of these sequences have facilitated functional annotation of the genome and the creation of several bioinformatic resources for the chicken. Recently, about 20 papers have been published on transcriptional profiling with DNA microarrays in chicken tissues under various conditions. Proteomics is another powerful high-throughput tool currently used for examining the dynamics of protein expression in chicken tissues and fluids. Computational analyses of the chicken genome are providing new insight into the evolution of gene families in birds and other organisms. Abundant functional genomic resources now support large-scale analyses in the chicken and will facilitate identification of transcriptional mechanisms, gene networks, and metabolic or regulatory pathways that will ultimately determine the phenotype of the bird. New technologies such as marker-assisted selection, transgenics, and RNA interference offer the opportunity to modify the phenotype of the chicken to fit defined production goals. This review focuses on functional genomics in the chicken and provides a road map for large-scale exploration of the chicken genome.

Marek's disease is a natural model for lymphomas overexpressing Hodgkin's disease antigen (CD30)