Proceedings of the 2019 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference

or oral presentation. A total of 19 papers were submitted and 6 were accepted (32% acceptance rate). All papers were anonymously peer-reviewed by at least two reviewers. A summary of the papers is as follows: Zheng Wang et al., “MASS: Protein Single-model global quality assessment using random forest and newly-designed statistical potentials”. This paper presents a singlemodel method named MASS for predicting global quality of individual protein models. The authors designed and re-implemented ten protein potentials and proved that these protein potentials are significantly different from each other. Using the values from ten potentials along with six other types of features, a random forest is trained to predict the global quality scores of individual models. MASS was evaluated along with other quality assessment methods in CASP11, CASP12, and CASP13 and the finding is that MASS outperforms most of the methods in CASP11 and is comparable with the leading methods in CASP12 and CASP13. Wren et al. BMC Bioinformatics 2020, 21(Suppl 4):254 Page 5 of 7


Introduction
The 16th Annual MidSouth Computational Biology and Bioinformatics Society (MCBIOS XVI) conference was held in Hilton Birmingham at University of Alabama Birmingham (UAB) conference center on March 28-30, 2019. The theme of the conference was Informatics for Precision Medicine. The co-chairs and conference hosts were Drs. Jake Y. Chen and Matthew Might from the University of Alabama Birmingham.
The program co-chairs were Dr. Weida Tong from the National Center for Toxicological Research at the Food and Drug Administration (NCTR/FDA) and Dr. Purushotham Bangalore from the University of Alabama Birmingham. The program (detailed below) included two tutorial workshops, 13 breakout oral presentations in seven different scientific tracks, two poster sessions, four keynote speakers, one roundtable discussion, one expert panel session, and two career development sessions. The workshop coordinators were Dr. Andy Crouse from UAB and Dr. Mary Yang from University of Arkansas Little Rock. The student outreach (career development) coordinators were Dr. Inimary Toby from University of Dallas, Dr. Brittany N. Lasseigne from HudsonAlpha, and student representative Ujwani Nukala from University of Arkansas.
A total of 168 people registered for the conference, including 82 professionals, 19 postdoctoral fellows, and 67 students. Among the 157 submitted abstracts, 75 were selected for oral presentations and 41 were selected for poster presentations. The poster session coordinator was Dr. Da Yan from UAB and the chair of the awards committee was Dr. Bindu Nanduri from Mississippi State University.
Executive officers and the new members of the Board of Directors were elected during a business luncheon. The MCBIOS new president this year was Dr. Weida Tong from NCTR/FDA and the President-Elect was chosen as Dr. Jake Y. Chen from UAB. In addition, two new Board members were elected: Drs. Steven Foley from NCTR/ FDA and Zhaohui "Steve" Qin from Emory University.
Tutorial 2: "Metabolomics Data Analysis", Instructor: Stephen Barnes, Ph.D., Professor Pharmacology & Toxicology at the University of Alabama at Birmingham (UAB). Awards MCBIOS young scientist excellence award MCBIOS Young Scientist Excellence" awards program recognizes students and postdoctoral fellows that exhibit scientific excellence in the field of Bioinformatics. Student and postdoctoral fellows go through a rigorous award application process and the top five candidates are selected to give an oral presentation in a session dedicated to this award program. This was the 3rd year for the "MCBIOS Young Scientist Excellence Award" program.

Breakout sessionsoral presentations
To compete, students and postdoctoral fellows submitted an abstract and a description of the innovation and their specific contribution to the research. Submissions were first evaluated and ranked by the MCBIOS board members and external judges who evaluated the application for the quality and impact of the research. The top 5 candidates were selected for the postdoctoral and student categories and were invited for an oral presentation in a special session during the second day of the conference. At that time, independent judges evaluated each talk to assess the quality, professionalism, creativity, dedication and multidisciplinary contribution. Judges at each stage of the award process, ensured that there was no conflict of interest (individual, institution etc). Monetary awards for the first, second and third place in student and post-doctoral categories were $200, $150 and $100 respectively. In addition to the monetary award, all the award winners for Young Scientist Excellence Award Winners were presented with an official MCBIOS certificate. Second Place, Tanmay Bera, Ph.D., NCTR/FDA, Jefferson, AR. "Improved imaging may help achieve better species level accuracy in identifying food contaminating beetles".

Poster presentation awards
The poster session was held from 4 pm to 5 pm on the first 2 days (March 28 and 29) of the meeting. Student and post-doctoral presenters presented their work at the poster sessions and it was judged for presentation quality by a panel of MCBIOS professional members that attended the conference. Monetary awards of $200 was given for the First place, $150 for Second place and $100 for the Third place.

Selecting papers for the MCBIOS proceedings
The MCBIOS XVI Proceedings contains work presented at MCBIOS 2019, either as an abstract or oral presentation. A total of 19 papers were submitted and 6 were accepted (32% acceptance rate). All papers were anonymously peer-reviewed by at least two reviewers. A summary of the papers is as follows: Zheng Wang et al., "MASS: Protein Single-model global quality assessment using random forest and newly-designed statistical potentials". This paper presents a singlemodel method named MASS for predicting global quality of individual protein models. The authors designed and re-implemented ten protein potentials and proved that these protein potentials are significantly different from each other. Using the values from ten potentials along with six other types of features, a random forest is trained to predict the global quality scores of individual models. MASS was evaluated along with other quality assessment methods in CASP11, CASP12, and CASP13 and the finding is that MASS outperforms most of the methods in CASP11 and is comparable with the leading methods in CASP12 and CASP13.
Hafez Eslami Manoochehri et al., "Drug-Target Interaction Prediction using semibipartite graph model and deep learning". This paper proposes a new framework for drug-target interaction prediction that learns latent features from drug-target interaction network. The problem is modeled as a semi-bipartite graph in which drug-drug and protein-protein similarities are also integrated. For each drug-target pair, an enclosing subgraph is extracted to capture the surrounding environment. Then, a graph labeling method is used for vertex ordering on each enclosing subgraph for adjacencymatrix based encoding. The embedding vectors are then used to train a deep neural network to predict drug-target interactions. The experiments showed that the proposed model can determine interaction likelihood for each drug-target pair and outperform other heuristics.
Mahmut Karakaya et al., Comparison of Smartphone-based Retinal Imaging Systems for Diabetic Retinopathy Detection using Deep Learning. The authors investigate the smartphone-based portable retinal imaging systems available on the market and compare their image quality and the automatic DR detection and the automatic DR detection accuracy using a deep learning framework. The authors observed that the network DR detection performance decreases as the field of view of the smartphone-based retinal systems get smaller where iNview is the largest and iExaminer is the smallest. The smartphone-based retina imaging systems can be used as an alternative to the direct ophthalmoscope.
King Jordan et al., Ancestry effects on type 2 diabetes genetic risk inference in Hispanic/Latino populations. The authors investigated how ancestry affects the inference of T2D genetic risk using PRS in diverse HL populations from Colombia and the United States (US). In Colombia, the authors compared T2D genetic risk for the Mestizo population of Antioquia to the Afro-Colombian population of Chocó, and in the US, they compared European-American versus Mexican-American populations. The experiments showed that T2D genetic risk in these HL populations is positively correlated with African and Native American ancestry and negatively correlated with European ancestry. The inferred relative risk of T2D is robust to differences in the ancestry of the cohorts used for variant discovery. Adam Thrash et al., Toward a More Holistic Method of Genome Assembly Assessment.
Assembly of full genome sequence is a key application of the high throughput sequencing technology. Traditionally, genome assemblies are assessed using statistics relating to contiguity of the assembly. In this paper, thrash et al. presents a review of problems that arise from relying solely on contiguity as a measure of genome assembly quality as well as current alternative methods. Alternative methods are compared on the basis of how informative they are about the biological quality of the assembly and how easy they are to use. A comprehensive method for using multiple metrics of measuring assembly quality is presented. Weaknesses and strengths of varying methods are presented and explained, with recommendations based on speed of analysis and user friendliness. The authors also offer a comprehensive method that incorporates multiple facets of quality assessment.
Yongsheng Bai et al., "MMiRNA-Viewer 2 , a Bioinformatics Tool for Visualizing Functional Annotation for MiRNA and MRNA Pairs in a Network". This paper presents an innovative bioinformatics tool, MMiRNA-Viewer 2 , for visualizing functional relationships between miRNA and mRNA pairs in a network utilizing the next generation sequencing data of miRNA and mRNA expression profiles in tumor and normal samples. The tool fills the gap that existing tools can not characterize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tumor and normal samples simultaneously. The tool takes mRNA and miRNA interaction pairs to display the mRNA and miRNA gene annotation information, signaling cascade pathways and direct cancer association between miRNAs and mRNAs. Functional annotation and gene regulatory information can be directly retrieved from the tool web server, which can help users quickly identify significant interaction sub-network and report possible disease or cancer association. The tool is applicable across a range of diseases and cancers and has advantages over existing tools.

Future meetings
The 17th Annual MCBIOS conference will be hosted by the SAS Institute in Cary, NC on April 26-28, 2021. The conference co-chairs are Drs. Weida Tong and Steven Foley from NCTR/FDA, and Dr. Inimary Toby from University of Dallas, TX.