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 …

Iteration Method For Predicting Essential Proteins Based On Orthology And Protein-Protein Interaction Networks, Wei Peng, Jianxin Wang, Weiping Wang, Qing Liu, Fang-Xiang Wu, Yi Pan

Computer Science Faculty Publications

Background: Identification of essential proteins plays a significant role in understanding minimal requirements for the cellular survival and development. Many computational methods have been proposed for predicting essential proteins by using the topological features of protein-protein interaction (PPI) networks. However, most of these methods ignored intrinsic biological meaning of proteins. Moreover, PPI data contains many false positives and false negatives. To overcome these limitations, recently many research groups have started to focus on identification of essential proteins by integrating PPI networks with other biological information. However, none of their methods has widely been acknowledged.

Results: By considering the facts that …

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 …

Efficient Error Correction For Next-Generation Sequencing Of Viral Amplicons, Pavel Skums, Zoya Dimitrova, David S. Campo, Gilberto Vaughan, Livia Rossi, Joseph C. Forbi, Jonny Yokosawa, Alexander Zelikovskiy, Yury Khudyakov

Computer Science Faculty Publications

Background: Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All …

The Offenders’ Perspective On Prevention: Guarding Against Victimization And Law Enforcement, Scott Jacques, Danielle Reynald

EBCS Articles

Law-abiding citizens are concerned with deterring and preventing crime. One strategy to accomplish this goal is to increase the costs and reduce the benefits that particular situations present to offenders. This form of crime control is known as situational crime prevention. Like law-abiding persons, offenders must concern themselves with being victimized. Differently, however, offenders must also worry about being detected and punished by formal agents. Thus, situational prevention from the offenders’ perspective is relatively complex, encompassing efforts to block not only opportunities for victimization but also for law enforcement. Building on the work of Clarke, the present study uses qualitative …