Physical Sciences and Mathematics Commons^™

Connectivity: Insights From The U.S. Long Term Ecological Research Network, David M. Iwaniec, Michael Gooseff, Katharine Suding, David Samuel Johnson, Daniel C. Reed, Debra Peters, Byron Adams, John E. Barrett, Brandon Bestelmeyer, Max C.N. Castorani, Elizabeth M. Cook, Melissa J. Davidson, Peter F. Groffman, Niall Hanan, Laura Huenneke, Pieter T.J. Johnson, Diane Mcknight, Robert J. Miller, Gregory Okin, Daniel Preston, Andrew Rassweiler, Chris Ray, Osvaldo Sala, Robert L. Schooley, Timothy Seastedt, Marko Spasojevic, Enrique R. Vivoni

Sustainable Futures Lab Publications

Ecosystems across the United States are changing in complex and surprising ways. Ongoing demand for critical ecosystem services requires an understanding of the populations and communities in these ecosystems in the future. This paper represents a synthesis effort of the U.S. National Science Foundation-funded Long-Term Ecological Research (LTER) network addressing the core research area of “populations and communities.” The objective of this effort was to show the importance of long-term data collection and experiments for addressing the hardest questions in scientific ecology that have significant implications for environmental policy and management. Each LTER site developed at least one compelling case …

Characterization Of Α-Anomeric Damaged Dna In Complex With Endonuclease Iv Using Fluorescence Resonance Energy Transfer (Fret), Beatrice Edjah

Georgia State Undergraduate Research Conference

No abstract provided.

Characterization Of Active Site Residues In Class I Nitronate Monooxygenase From Pseudomonas Aeruginosa Pao1, Christopher Aguillon

Georgia State Undergraduate Research Conference

No abstract provided.

Hydration Site Of Cyclophilin A And Its Allosteric Effects On The Enzyme's Function, Abdullah Shouaib, Jonathan Lopez

Georgia State Undergraduate Research Conference

No abstract provided.

A Novel Computational Approach For Reducing False Positives In Text Data Mining, Noah Yasarturk

Georgia State Undergraduate Research Conference

No abstract provided.

Memory Consolidation In Binary Inputs, Shateil C. French Mr., Ricardo J T Toscano

Georgia State Undergraduate Research Conference

No abstract provided.

Analysis Of New Hiv-1 Inhibitors As Potential Antiviral Agents For Hiv-2, Rowan Brothers

Georgia State Undergraduate Research Conference

No abstract provided.

Multistability And Its Occurrence In Neurons Within The Pre-Bötzinger Complex, Alex Vargas

Georgia State Undergraduate Research Conference

No abstract provided.

Direct Chemical Control Of Pu.1, A Hematopoietic Regulator, Noa Erlitzki

Georgia State Undergraduate Research Conference

No abstract provided.

Complementary Effect Of Electrical And Inhibitory Coupling In Bursting Synchronization, Kevin Daley

Georgia State Undergraduate Research Conference

gsurc 2015

Quantitative And Qualitative Stability Analysis Of Polyrhythmic Circuits, Drake Knapper

Georgia State Undergraduate Research Conference

No abstract provided.

Functional Organization And Restoration Of The Brain Motor-Execution Network After Stroke And Rehabilitation, Sahil Bajaj, Andrew Butler, Daniel Drake, Mukesh Dhamala

Physics and Astronomy Faculty Publications

Multiple cortical areas of the human brain motor system interact coherently in the low frequency range (<0.1 Hz), even in the absence of explicit tasks. Following stroke, cortical interactions are functionally disturbed. How these interactions are affected and how the functional organization is regained from rehabilitative treatments as people begin to recover motor behaviors has not been systematically studied. We recorded the intrinsic functional magnetic resonance imaging (fMRI) signals from 30 participants: 17 young healthy controls and 13 aged stroke survivors. Stroke participants underwent mental practice (MP) or both mental practice and physical therapy (MP+PT) within 14–51 days following stroke. We investigated the network activity of five core areas in the motor-execution network, consisting of the left primary motor area (LM1), the right primary motor area (RM1), the left pre-motor cortex (LPMC), the right pre-motor cortex (RPMC) and the supplementary motor area (SMA). We discovered that (i) the network activity dominated in the frequency range 0.06–0.08 Hz for all the regions, and for both able-bodied and stroke participants (ii) the causal information flow between the regions: LM1 and SMA, RPMC and SMA, RPMC and LM1, SMA and RM1, SMA and LPMC, was reduced significantly for stroke survivors (iii) the flow did not increase significantly after MP alone and (iv) the flow among the regions during MP+PT increased significantly. We also found that sensation and motor scores were significantly higher and correlated with directed functional connectivity measures when the stroke-survivors underwent MP+PT but not MP alone. The findings provide evidence that a combination of mental practice and physical therapy can be an effective means of treatment for stroke survivors to recover or regain the strength of motor behaviors, and that the spectra of causal information flow can be used as a reliable biomarker for evaluating rehabilitation in stroke survivors.

Statistical Analysis Of Enhanced Ctl Killing Activity Against Irradiated Tumor Cells, Catannian Sanogo

Georgia State Undergraduate Research Conference

No abstract provided.

The Effect Of The R1648h Sodium Channel Mutation On Neuronal Excitability: A Model Study, Christopher Locandro, Robert Clewley

Georgia State Undergraduate Research Conference

No abstract provided.

Development Of Novel Inhibitors Targeting Epigenetic Enzymes, Johnny Truong, Leilei Yan Dr., Brandon Canup, Kun Qian, George Y. Zheng Dr.

Georgia State Undergraduate Research Conference

No abstract provided.

Resiliency To Bistability In The Neurons From The Pre-Bötzinger Complex, Treadwell D. Singfield Ii

Georgia State Undergraduate Research Conference

No abstract provided.

A New Essential Protein Discovery Method Based On The Integration Of Protein-Protein Interaction And Gene Expression Data, Min Li, Hanhui Zhang, Jian-Xin Wang, Yi Pan

Computer Science Faculty Publications

The article offers information on a study conducted on the essential protein discovery method, PeC, which is based on the integration of protein-protein interaction and gene expression data. It states that PeC was developed on the basis of the definitions of edge clustering coefficient (ECC) and Pearson's correlation coefficient (PCC). It mentions that a list of essential proteins of Saccharomyces cerevisiae were collected.

Background: Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have …

Towards The Identification Of Protein Complexes And Functional Modules By Integrating Ppi Network And Gene Expression Data, Min Li, Xuehong Wu, Jianxin Wang, Yi Pan

Computer Science Faculty Publications

Background: Identification of protein complexes and functional modules from protein-protein interaction (PPI) networks is crucial to understanding the principles of cellular organization and predicting protein functions. In the past few years, many computational methods have been proposed. However, most of them considered the PPI networks as static graphs and overlooked the dynamics inherent within these networks. Moreover, few of them can distinguish between protein complexes and functional modules.

Results: In this paper, a new framework is proposed to distinguish between protein complexes and functional modules by integrating gene expression data into protein-protein interaction (PPI) data. A series of time-sequenced subnetworks …

Trip: A Method For Novel Transcript Reconstruction From Paired-End Rna-Seq Reads, Serghei Mangul, Adrian Caciula, Dumitru Brinza, Ion I. Măndoiu, Alexander Zelikovskiy

Computer Science Faculty Publications

Preliminary experimental results on synthetic datasets generated with various sequencing parameters and distribution assumptions show that TRIP has increased transcriptome reconstruction accuracy compared to previous methods that ignore fragment length distribution information.

Guest Editors' Introduction, Jianer Chen, Ion Măndoiu, Raj Sunderraman, Jianxin Wang, Alexander Zelikovskiy

Computer Science Faculty Publications

This Supplement includes a selection of papers presented at the 7th International Symposium on Bioinformatics Research and Application (ISBRA), which was held on May 27-29, 2011 at Central South University in Changsha, China. The technical program of the symposium included 36 extended abstracts presented orally and published in volume 6674 of Springer Verlag’s Lecture Notes in Bioinformatics series. Additionally, the program included 38 short abstracts presented either orally or as posters. Authors of both extended and short abstracts presented at the symposium were invited to submit full versions of their work to this Supplement. Following a rigorous review process, 19 …

Voltage Oscillations And Response Dynamics In A Model Of Sensory Hair Cells, Alexander B. Neiman, Kai Dierkes, Benjamin Lindner, Andrey Shilnikov

Neuroscience Institute Faculty Publications

We used a Hodgkin-Huxley type model of the basolateral ionic currents of bullfrog sacculus to study genesis of spontaneous voltage oscillation patterns and how the spontaneous oscillations shape the response of the hair cell to external mechanical stimuli.

Phase-Lag Return Mappings For A 3 Cell Multifunctional Central Pattern Generator, Jeremy Wojcik, Robert Clewley, Andrey Shilnikov

Neuroscience Institute Faculty Publications

We describe and expand on a novel computational approach to reduce detailed models of central pattern generation to equationless return mapping for the phase lags between the constituting bursting interneurons.

Classification And Visualization Of Neural Patterns Using Subspace Analysis Statistical Methods, Jun Xia, Marius Osan, Emilia Titan, Riana Nicolae, Remus Osan

Neuroscience Institute Faculty Publications

The size and complexity of neural data is increasing at a dramatic pace due to rapid advances in experimental technologies. As a result, the data analysis techniques are shifting their focus from single-units to neural populations. The goal is to investigate complex temporal and spatial patterns, as well as to present the results in an intuitive way, allowing for detection and monitoring of relevant neural patterns.

Fishing For Animal Rights In The Cove: A Holistic Approach To Animal Advocacy Documentaries, Carrie Packwood Freeman

Communication Faculty Publications

The Oscar-winning 2009 documentary The Cove serves as a thrilling and poignant advocacy tool promoting activism to save free-roaming dolphins off the coast of Japan from kidnapping, enslavement in marine parks, and slaughter for meat. This essay evaluates the ethical and social justice implications of The Cove not just for dolphins but for the animal rights movement as a whole, particularly in terms of how it could challenge the ethicality of humans killing any nonhuman animals for food. Strategic media recommendations are made for how animal protection advocates could better deconstruct the human/animal dualism that is at the root of …

Six Types Of Multistability In A Neuronal Model Based On Slow Calcium Current, Tatiana Malashchenko, Andrey Shilnikov, Gennady Cymbalyuk

Neuroscience Institute Faculty Publications

Background: Multistability of oscillatory and silent regimes is a ubiquitous phenomenon exhibited by excitable systems such as neurons and cardiac cells. Multistability can play functional roles in short-term memory and maintaining posture. It seems to pose an evolutionary advantage for neurons which are part of multifunctional Central Pattern Generators to possess multistability. The mechanisms supporting multistability of bursting regimes are not well understood or classified.

Methodology/Principal Findings: Our study is focused on determining the bio-physical mechanisms underlying different types of co-existence of the oscillatory and silent regimes observed in a neuronal model. We develop a low-dimensional model typifying the dynamics …

Her2 Targeted Molecular Mr Imaging Using A De Novo Designed Protein Contrast Agent, Jingjuan Qiao, Shunyi Li, Lixia Wei, Jie Jiang, Robert Long, Hui Mao, Ling Wei, Liya Wang, Hua Yang, Hans E. Grossniklaus, Zhi-Ren Liu, Jenny J. Yang

Chemistry Faculty Publications

The application of magnetic resonance imaging (MRI) to non-invasively assess disease biomarkers has been hampered by the lack of desired contrast agents with high relaxivity, targeting capability, and optimized pharmacokinetics. We have developed a novel MR imaging probe targeting to HER2, a biomarker for various cancer types and a drug target for anti-cancer therapies. This multimodal HER20targeted MR imaging probe integrates a de novo designed protein contrast agent with a high affinity HER2 affibody and a near IR fluorescent dye. Our probe can differentially monitor tumors with different expression levels of HER2 in both human cell lines and xenograft mice …

Integration Of Breast Cancer Gene Signatures Based On Graph Centrality, Jianxin Wang, Gang Chen, Min Li, Yi Pan

Computer Science Faculty Publications

Background: Various gene-expression signatures for breast cancer are available for the prediction of clinical outcome. However due to small overlap between different signatures, it is challenging to integrate existing disjoint signatures to provide a unified insight on the association between gene expression and clinical outcome.

Results: In this paper, we propose a method to integrate different breast cancer gene signatures by using graph centrality in a context-constrained protein interaction network (PIN). The context-constrained PIN for breast cancer is built by integrating complete PIN and various gene signatures reported in literatures. Then, we use graph centralities to quantify the importance of …

Parallel Progressive Multiple Sequence Alignment On Reconfigurable Meshes, Ken Nguyen, Yi Pan, Ge Nong

Computer Science Faculty Publications

Background: One of the most fundamental and challenging tasks in bio-informatics is to identify related sequences and their hidden biological significance. The most popular and proven best practice method to accomplish this task is aligning multiple sequences together. However, multiple sequence alignment is a computing extensive task. In addition, the advancement in DNA/RNA and Protein sequencing techniques has created a vast amount of sequences to be analyzed that exceeding the capability of traditional computing models. Therefore, an effective parallel multiple sequence alignment model capable of resolving these issues is in a great demand.

Results: We design O(1) run-time solutions …

A Comparison Of The Functional Modules Identified From Time Course And Static Ppi Network Data, Xiwei Tang, Jianxin Wang, Binbin Liu, Min Li, Gang Chen, Yi Pan

Computer Science Faculty Publications

Background: Cellular systems are highly dynamic and responsive to cues from the environment. Cellular function and response patterns to external stimuli are regulated by biological networks. A protein-protein interaction (PPI) network with static connectivity is dynamic in the sense that the nodes implement so-called functional activities that evolve in time. The shift from static to dynamic network analysis is essential for further understanding of molecular systems.

Results: In this paper, Time Course Protein Interaction Networks (TC- PINs) are reconstructed by incorporating time series gene expression into PPI networks. Then, a clustering algorithm is used to create functional modules from three …

Inferring Viral Quasispecies Spectra From 454 Pyrosequencing Reads, Irina Astrovskaya, Bassam Tork, Serghei Mangul, Kelly Westbrooks, Ion Măndoiu, Peter Balfe, Alexander Zelikovskiy

Computer Science Faculty Publications

Background: RNA viruses infecting a host usually exist as a set of closely related sequences, referred to as quasispecies. The genomic diversity of viral quasispecies is a subject of great interest, particularly for chronic infections, since it can lead to resistance to existing therapies. High-throughput sequencing is a promising approach to characterizing viral diversity, but unfortunately standard assembly software was originally designed for single genome assembly and cannot be used to simultaneously assemble and estimate the abundance of multiple closely related quasispecies sequences.

Results: In this paper, we introduce a new Viral Spectrum Assembler (ViSpA) method for quasispecies spectrum reconstruction …