Genomic studies of complex behavior: The Arbeitman lab studies the molecular-genetic basis of complex behavior using Drosophila melanogaster as a model. The Drosophila model system has some of the most sophisticated tools to understand behavior with cell-type resolution, given that the neurons that underlie complicated reproductive behaviors have been identified using molecular tools. Students can participate on computational studies of genomic data sets that were generated to understand complex reproductive behaviors. The student should have familiarity with genetic and molecular biology concepts and should be able to work independently using python and R programming tools.
Contact: Dr. Michelle Arbeitman
Functional Genomics in Maize: Analysis of maize genomic and epigenomic data in maize. Ongoing projects include chromatin structure profiling, analysis of genomic G-quadruplex motifs, or computational analysis of 3D images of nuclei. Student should be fluent in unix, file manipulation, and adept at self-teaching from online documentation of commonly used bioinformatic tools. Student should also have good organizational and note-taking skills along with a basic knowledge of genetics and biology.
Contact: Dr. Hank Bass
Nucleosome Organization in Development and Disease: The objective of work in the Dennis lab is to characterize the changes in nucleosome organization in development and disease. We have shown that chromatin regulatory proteins control widespread and transient remodeling events that result in altered nucleosome sensitivities that define the potential of the cell. Internships in the Dennis lab will use computational approaches to facilitate an integrated analysis of dynamic nucleosome remodeling and nucleosome sensitivity. These studies will yield immediate and widely applicable information on the fundamental biology of complex genomes and ultimately new approaches for understanding development and disease.
Contact: Dr. Jonathan Dennis
Epigenetic basis of neuropsychiatric disorders by using mouse models: Epigenetic regulation has recently emerged as an underpinning mechanim of brain disorders, particularly neuropsychiatric diseases. We will utilize cutting edge epi/genomic tools to decipher out novel epigenetic mechanims with an interdesciplinary intergration with behavioral neuroscience. We are particularly interested in the roles of non-coding RNAs and newly defined DNA epigenetic modifications in drug addiction and depression by using mouse models. A basic knowledge of biology and genetics and skills of computation programing are required. You will have an opportunity to work on the next generation sequencing data analyses (DNA methylation seq, mRNAseq, small RNAseq, ChIPseq) within and beyond the laboratory.
Contact: Dr. Jian Feng
Chromosome Structure and Function: Assist in the analysis of large genomic data sets aimed at understanding the organization of chromosomes during stem cell differentiation and abnormalities in cancer (pediatric acute lymphocytic leukemia). Student will be expected to have experience with linux command line, R or Python, and basic knowledge of DNA structure, chromosomes and chromatin.
Contact: Dr. David Gilbert
Ecological, evolutionary, and behavioral genomics: Analyze genetic and genomic data that addresses fundamental questions such as, “why are individuals within species so genetically diverse, and what genetic, ecological and evolutionary processes promote that diversity?” Student is expected to have experience with linux command line and shell scripting, at least one coding language such as C/C++, Python, or R, basic knowledge of genomes and genome structure, and the ability to solve problems independently.
Contact: Dr. Kim Hughes
Development and evolution of Drosophila: Opportunities for students to work on modeling, simulation, visualization or data analysis on genomic and phenotypic data on the relationship between development and evolution in the fruit fly, Drosophila melanogaster. We can take advantage of a variety of your skills, including programming, bioinformatics or statistics. Students should have background in genetics and preferably evolutionary biology.
Contact: Dr. David Houle
Transcription and gene expression in plants: The McGinnis Lab studies epigenetic gene regulation in maize. Computational biology students would assist with our research by participating in analysis of RNA-seq, ChIP-seq and other large datasets. Recent and ongoing projects include co-expression analysis, identification of regulatory RNAs, and relating expression changes with epigenetic data. Students should have a basic knowledge of molecular biology and an independent working knowledge of informatics and programming (R and Python) tools and approaches.
Contact: Dr. Karen McGinnis
Venom Genomics and Evolution: Venom Genomics and Evolution: Students will analyze genomic, transcriptomic, and proteomic data to characterize venom composition and the genetic basis of adaptation in venoms of snakes, scorpions, and centipedes. Students will be expected to be comfortable working at a linux command line and coding in Python and be familiar with basic molecular biology and biochemistry.
Contact: Dr. Darin Rokyta
High-Resolution Cryogenic Electron Microscopy: Help develop tools for high-throughput high-resolution 3D structure determination of medically relevant biomolecules. Student will be expected to have experience with linux, Python, or development of web based software.
Contact: Dr. Scott Stagg
Functional Genomics Research: The Center for Genomics and Personalized Medicine (CGPM) serves FSU researchers through collaborations in the generation and analysis of large and diverse genomics data sets. The Center works in a wide variety of research areas related to functional genomics, including projects investigating how gene expression, chromatin structure, and replication timing influence phenotypes and cellular responses. Students will have the opportunity to perform wet bench and/or computational genomics research. Students interested in computational research are expected to be comfortable with the unix command line, have some programming experience, and have a basic understanding of concepts in genetics and probability. All interested students should be highly self-motivated and have the ability to perform independent self-driven learning for the purpose of creative problem solving and establishing knowledge in a given research area.
Contact: Dr. Daniel Vera
Computer Simulation of Biomolecules: Physics-Based Drug Discovery; Biomolecular Recognition; Protein Functional Dynamics. Students will apply our state-of-the-art molecular dynamics simulation methods on cutting-edge computing facilities.
Contact: Dr. Wei Yang
High-performance Computational Biology: Dr. Weikuan Yu has an interest in high-performance computational biology research. In prior research projects, he has investigated various approaches to improve the performance of computational mass finger-printing, cloud-based fast k-mer counting for next-generation sequencing (NGS) data analysis and evaluation of NGS tools for meta-genomics.
Contact: Dr. Weikuan Yu