The MCBIOS 2004 conference brought together regional researchers and students in biology, computer science and bioinformatics on October 7th-9th 2004 to present their latest work. This editorial describes the conference itself and introduces the twelve peer-reviewed manuscripts accepted for publication in the Proceedings of the MCBIOS 2004 Conference. These manuscripts included new methods for analysis of high-throughput gene expression experiments, EST clustering, analysis of mass spectrometry data and genomic analysi

AA Ptitsyn

E Marshall

H Fang

H Hong

JD Wren

Jonathan D Wren

L Shi

NR Garge

PK Tan

Q Xie

RL Frank

RR Delongchamp

SF Jennings

William Slikker

Y Tang

Z Xu

BMC Bioinformatics

English

PubMed

Crossref

Proceedings of the Second Annual Conference of the MidSouth Computational Biology and Bioinformatics Society

Abstract The MCBIOS 2004 conference brought together regional researchers and students in biology, computer science and bioinformatics on October 7th-9th 2004 to present their latest work. This editorial describes the conference itself and introduces the twelve peer-reviewed manuscripts accepted for publication in the Proceedings of the MCBIOS 2004 Conference. These manuscripts included new methods for analysis of high-throughput gene expression experiments, EST clustering, analysis of mass spectrometry data and genomic analysis</p

Slikker William

Wren Jonathan D

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BioMed CentralBMC Bioinformatics
ssOpen AcceProceedings
Proceedings of the Second Annual Conference of the MidSouth 
Computational Biology and Bioinformatics Society
Jonathan D Wren1 and William Slikker Jr*2
Address: 1Advanced Center for Genome Technology, Stephenson Research and Technology Center, Department of Botany and Microbiology, 101 
David L. Boren Blvd., The University of Oklahoma, Norman Oklahoma 73019, USA and 2Deputy Director for Research, National Center for 
Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA
Email: Jonathan D Wren - Jonathan.Wren@OU.edu; William Slikker* - wslikker@nctr.fda.gov
* Corresponding author    
bioinformaticsconferencesMCBIOSISCB
Abstract
The MCBIOS 2004 conference brought together regional researchers and students in biology,
computer science and bioinformatics on October 7th-9th 2004 to present their latest work. This
editorial describes the conference itself and introduces the twelve peer-reviewed manuscripts
accepted for publication in the Proceedings of the MCBIOS 2004 Conference. These manuscripts
included new methods for analysis of high-throughput gene expression experiments, EST
clustering, analysis of mass spectrometry data and genomic analysis
Introduction
The MidSouth Computational Biology and Bioinformat-
ics Society (MCBIOS) was formed to advance the under-
standing of bioinformatics and computational biology by
bringing together scientists of various backgrounds and
disciplines and facilitating the collaboration of research-
ers with similar and complementary backgrounds to solve
biological, health, and/or medical problems. MCBIOS
also aims to promote education in bioinformatics and
computational biology, informing the general public of
the results and implications of current research in bioin-
formatics and computational biology, and promote other
activities that will contribute to the development of bioin-
formatics and computational biology within the mid-
south region of the United States [1]. MCBIOS especially
supports, encourages, and mentors its student members.
The Second Annual MCBIOS conference was held at the
Peabody Hotel in Little Rock, Arkansas, on October 7–9,
2004. With a unifying theme of "Bioinformatics: A Sys-
tems Approach," the conference featured three days of sci-
entific platform presentations, posters, and panel
discussions in addition to a business meeting and an
Arkansas BRIN Research Symposium. Dr. Michael Grib-
skov, President of the International Society for Computa-
tional Biology (ISCB), and Dr. Alan Leshner, CEO of the
American Association for the Advancement of Science
(AAAS) and the Executive Publisher of Science, provided
the keynote addresses. Dr. Gribskov's invigorating presen-
tation focused on the history, development and future of
systems biology and bioinformatics; Dr. Leshner's out-
standing lecture on the role of science in society had the
participants enthralled.
Proceedings summary
Student platform and poster competitions were con-
ducted and judges determined several outstanding presen-
tations from among many excellent ones. Awards for
platform (oral) presentations were given to Philip Wil-
liams of the University of Arkansas at Little Rock, Jennifer
from Second Annual MidSouth Computational Biology and Bioinformatics Society Conference. Bioinformatics: a systems approach
Little Rock, AR, USA, 7–9 October 2004
Published: 15 July 2005
BMC Bioinformatics 2005, 6(Suppl 2):S1 doi:10.1186/1471-2105-6-S2-S1
<supplement> <title> <p>Second Annual MidSouth Computational Biology and Bioinformatics Society Conference. Bioinformatics: a systems approach</p> </title> <editor>William Slikker, Jr and Jonathan D Wren</editor> <note>Proceedings</note> </supplement>Page 1 of 4
(page number not for citation purposes)
BMC Bioinformatics 2005, 6(Suppl 2):S1Roller of Hendrix College, and Yong Tang of the Univer-
sity of Arkansas at Little Rock. Awards for outstanding
poster presentations were given to Yong Tang of the Uni-
versity of Arkansas at Little Rock, Sudeepa Bhattacharyya
of the University of Arkansas at Little Rock and Phillip
Romero of the University of New Orleans. These awards
were underwritten by the Arkansas Biomedical Research
Infrastructure Network (BRIN) program and funded
through the National Institutes of Health's NCRR Divi-
sion of Research Infrastructure. The US Food and Drug
Administration's National Center for Toxicological
Research provided additional valuable financial support.
Papers submitted for inclusion in these proceedings were
peer-reviewed by two or more program committee mem-
bers and external experts as necessary. The accepted papers
reflect the innovative bioinformatics approaches being
undertaken in the region. Several categories of research
focus are apparent in the papers:
Transcriptional Analysis using Microarrays
Zengjun "Alex" Xu and colleagues [2] employ microarray
analysis in combination with a battery of bioinformatics
tools and make inroads into better understanding Parkin-
son's Disease (PD). PD is often studied using PC12 cells,
which produce dopamine, in combination with 1-methyl-
4-phenylpyridinium (MPP+), which depletes dopamine
content and elicits cell death in PC12 cells, much as is
observed in PD. To identify the important genes affected
in PC12 cells by MPP+, Xu et al identified 106 genes with
differential expression levels. The genes were tied back to
their ontological categories and implicated the oxidative
stress and apoptosis pathways as playing a role in the
observed effects. Examining these responders in terms of
their literature-based associations [3], the DNA-damage
pathway is identified as the likely primary culprit. Several
genes are also implicated as central in this process with
only loose literature ties to PD and MPP+, suggesting fruit-
ful avenues of future experimental pursuit.
Bob Delongchamp et al [4] present the statistical design
and analysis of a study to estimate gene expression differ-
ences between male and female livers. Addressing varia-
tion attributable to sample processing, arrays,
hybridizations, normalization, and subjects, their statisti-
cal analysis suggested that about 224 genes of the 31,110
interrogated genes were expressed differentially depend-
ing upon gender. However, these differences were small
and it was not possible to specify sets of differentially
expressed genes that do not have large false discovery
rates. The paper offers a comprehensive and statistically
rigorous approach to summarizing genome-wide interro-
gation of gene expression changes.
Hong Fang et al [5] also focused upon the human liver
and used a variety of bioinformatics approaches to exam-
ine microarray expression profiles from liver neoplasms
that arise in albumin-SV40 transgenic rats to elucidate
genes, chromosome aberrations and pathways that might
be associated with human liver cancer. Their analysis
implicates human chromosomes 10, 11 and 19 as regions
of potential chromosomal aberrations.
Microarray-based measurements of mRNA abundance
and ratio calculations assume a linear relationship
between the fluorescence intensity and the dye concentra-
tion. By scanning a microarray scanner calibration slide
containing known concentrations of fluorescent dyes
under various PMT gains, Leming Shi et al. [6] demon-
strated the dramatic differences in calibration characteris-
tics of Cy5 and Cy3, indicating the importance of
scanning microarrays at fixed, optimal gain settings under
which the linearity between concentration and intensity is
maximized. Combined with simulation results, they pro-
vided rational explanations to the existence of ratio
underestimation, intensity-dependence of ratio bias, and
anti-correlation of ratios in dye-swap replicates. Although
normalization methods improve reproducibility of
microarray measurements, they appear less effective in
improving accuracy. A method of calculating ratios based
on concentrations estimated from the calibration curves
was proposed for correcting ratio bias.
In another paper, Leming Shi et al re-evaluate a study by
Tan et al [7], which was extensively cited in a recent Science
paper [8], that paints a very negative picture of the cross-
platform comparability, and, hence, the reliability of
microarray technology. Shi et al [9] reanalyzed Tan's data-
set and found that the low cross-platform concordance
reported in Tan's study appears to be mainly due to a com-
bination of low intra-platform consistency and a poor
choice of data analysis procedures, instead of inherent
technical differences among different platforms. They
emphasize the importance of establishing calibrated RNA
samples and reference datasets to objectively assess the
performance of different microarray platforms. They also
discuss how the proficiency of individual laboratories can
affect results as well as the merits of various data analysis
procedures.
EST Clustering
The accuracy of clustering ESTs from a large dataset repre-
senting a single species can be assessed by first clustering
known genes (mRNAs) for that species to produce a non-
overlapping gene set. Frank and Ercal [10] report a new
algorithm for the analysis of Glycine max and suggest that
gene family identification may be facilitated by using a
hierarchical clustering method that incrementally
increases the stringency of sequence matching, while Ptit-Page 2 of 4
(page number not for citation purposes)
BMC Bioinformatics 2005, 6(Suppl 2):S1syn and Hide [11] report the design of an EST clustering
program that is more efficient than its predecessors and
make their software freely available to the public on an
open-source basis.
In cluster analysis, however, there is no null hypothesis to
test and no 'right answer'. Methodologists have suggested
that the validity of clustering methods should be based on
classifications that yield reproducible findings beyond
chance levels. Nikhil Garge et al [12] evaluated perform-
ance of four commonly used non-hierarchical clustering
algorithms (SOM, K-means, CLARA, and Fuzzy C-means)
on 37 microarray datasets and found a low stability for all
four algorithms even at the elevated sample sizes of n =
50. K-means showed more replicable performance than
the other clustering algorithms.
Proteomics and Mass Spectrometry
The combination of chemical crosslinking and mass spec-
trometry (MS) provides a powerful approach to analyze
protein-protein and protein-oligonucleotide interaction
sites, but the computational challenge lies in being able to
effectively choose among the many different possible
interpretations of MS data. Yong Tang et al [13] report the
design of an algorithm (CLPM, for Cross-Linked Peptide
Mapping) that matches peptide masses determined exper-
imentally with theoretical peptides which could have
been produced as by-products of these crosslinking reac-
tions.
Huixiao Hong et al [14] report a method to reliably meas-
ure the similarities among SELDI mass spectra for quality
control to decrease noise in proteomic profiling data prior
to analysis. The study investigated the reproducibility of
SELDI experiments and systematic variability between
plates, chips, and spots on which the samples were
assayed using SELDI based proteomic procedures.
Genomic Analysis
The ever-expanding amount of genomic data provides a
challenge in making observations about correlated fea-
tures. Jonathan Wren et al [15] present an approach to
standardize genomic data in a sequence matrix format
and iteratively search for correlated features using Monte
Carlo simulations to rearrange the features and report
items with distributions that differ significantly from ran-
dom allocation. Their approach is strongly limited by
computational processing power and memory considera-
tions, but the successful identification of known correla-
tions with this approach lays the foundation for
automating future exploration of genomic features.
Qian Xie et al [16] developed a novel adaptation of the
Decision Forest pattern recognition method named Deci-
sion Forest for SNPs (DF-SNPs). Their DF-SNPs method
was used to differentiate esophageal squamous cell carci-
noma cases from controls, based on individual SNPs, SNP
types and SNP patterns. Their method holds promise in
identifying potential biomarkers from SNP data and com-
plementing existing methods for genotype analyses.
Summary of subchapter meetings
Since its inception, MCBIOS has tried to foster local chap-
ters to provide more frequent contact for the membership.
Currently three chapters are active: The Central Arkansas
Chapter (which hosted the first two MCBIOS annual con-
ferences), the Louisiana Chapter (which will host the next
two MCBIOS annual conferences), and the Oklahoma
Chapter. As one of the most active local chapters, the
Oklahoma Chapter, which goes by the name of the Okla-
homa Bioinformatics Society, hosted its own successful
symposium, OKBIOS 2004, on November 12th, 2004. A
total of 228 people pre-registered for the conference, 31
more registered on site, and a total of 146 people
attended. Participants came from all the major Oklahoma
universities, companies, government agencies, regional
colleges and even a few from high schools. A very interest-
ing group of invited speakers (9 speakers, including one
who spoke through an interactive Internet videoconfer-
ence) presented on a diverse range of topics, encompass-
ing academic, government and commercial efforts in
bioinformatics. More than half the participants turned in
a conference evaluation form and judging from the very
positive feedback, OKBIOS 2004 was a success. On a one
to five scale with five being the highest satisfaction level,
the average overall rating for the symposium was 4.4
(51% of participants turned in evaluations). Feedback
suggested that participants especially enjoyed hearing
about bioinformatics efforts and challenges from within
non-academic sectors in addition to the academic talks.
Vendors included ISC Bioexpress, who provided two door
prizes for filling out evaluations and Silicon Genetics,
who sponsored the student poster awards. In total,
research groups from various Oklahoma institutions sub-
mitted 16 posters and 5 oral presentations, with 3 of those
oral presentations being selected for presentation at the
conference by the program committee. The program com-
mittee for OKBIOS 2004 consisted of Jonathan Wren
(OU), Yuriy Gusev (OUHSC), Michelle Wiginton (OU),
Sanjay Bidichandani (OUHSC), Patricia Ayoubi (OSU)
and Ulrich Melcher (OSU). Organizers were invited to
hold a related symposium on Synthetic Biology the day
prior, which had approximately 70 participants and was
also well received, making it a two-day event of bioinfor-
matics-related symposia.
Future Meetings
The third annual MCBIOS Conference will be held in
Baton Rouge, Louisiana, on Thursday and Friday, Novem-
ber 17-8, 2005 at the beautiful Pennington BiomedicalPage 3 of 4
(page number not for citation purposes)
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Research Center. The fourth annual MCBIOS Conference
is scheduled to be held in New Orleans, Louisiana in
2006. Further information about MCBIOS can be found
at our web site: http://www.MCBIOS.org. MCBIOS is a
regional affiliate of the International Society for Compu-
tational Biology http://www.ISCB.org.
Acknowledgements
We thank the Program Committee members including Steve Jennings, Jen-
nifer Leopold, Anne Maglia, Mariofanna Milanova, Andrey Ptitsyn, Yuriy 
Gusev, Xiaowei Xu, Russel Bruhn, Tom Kieber-Emmons and Weida Tong 
for their dedication and efforts to peer review the abstracts and manu-
scripts submitted by the attendees. Appreciation also goes to the Arkansas 
BRIN program funded by NIH's National Center for Research Resources 
(grant #P20 RR-16460), the University of Arkansas at Little Rock, the Mid-
South Bioinformatics Center, the National Center for Toxicological 
Research/FDA, and the University of Arkansas Medical Sciences for sup-
port of the second annual conference of the MidSouth Computational Biol-
ogy and Bioinformatics Society. OKBIOS 2004 was made possible by a 
subaward from NIH INBRE grant # P20RR016478-04.
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AJ: Genome-wide estimation of gender differences in the gene expression of human livers: Statistical design and analysis.

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Ercal F: Evaluation of Glycine max mRNA clusters.

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Hide W: CLU: A new algorithm for EST clustering.

HR: Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network. Bioinformatics

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SF: CLPM: A Cross-Linked Peptide Mapping Algorithm for Mass Spectrometric Analysis.

Slikker W: A microarray study of MPP+-treated PC12 cells: Mechanisms of toxicity (MOT) analysis using bioinformatics tools.

Tong W: Decision Forest Analysis of 61 Single Nucleotide Polymorphisms in a Case-Control Study of Esophageal Cancer; a novel method.

Tong W: Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).

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http://doaj.org/search?source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3A%7B%22id%22%3A%228130a0d66c2e45dd8e6d00e98f971f64%22%7D%7D%5D%7D%7D%7D

Proceedings of the Second Annual Conference of the MidSouth Computational Biology and Bioinformatics Society

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