Physical Sciences and Mathematics Commons^™

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 …