Life Sciences Commons^™

Early Seed Development Responses In Cereals Under Environmental Stresses, Kevin Begcy

Kevin Begcy

Plants are influenced by a large number of environmental factors. The search for higher yields at lower costs requires detailed knowledge of physiology, biochemistry, molecular and genetic level of plants, in order to optimize the relationship between different factors of production for maximum performance. Reproductive development has been demonstrated to be especially highly sensitive to environmental stresses. Within environmental stresses, drought and heat stress are the major restrictors of food production worldwide. With decreasing supplies of freshwater, increase in average temperature and predictions for the increased frequency of extreme precipitation events, there is a critical need for developing crops that …

Effectiveness Of Group Kickboxing As A Means To Improve Gait And Balance In Individuals With Ms, Kurt Jackson, Kimberly Edginton Bigelow, Christina Cooper, Harold L. Merriman

Harold L. Merriman

In recent years, there has been a particular emphasis on identifying and delivering appropriate therapeutic interventions that address the significant balance and gait impairments that affect individuals with multiple sclerosis (MS). Group interventions implemented in community settings have been especially of interest, including tai chi classes. Recently, the authors conducted a preliminary study to examine whether group kick-boxing, which requires more vigorous movements, might be a feasible intervention. Initial findings showed promise and led the authors to pursue a more rigorous follow-up study, with the objective of determining whether a 5-week group kickboxing class improved clinical measures of balance and …

Complete Genome Sequence Of Spiroplasma Turonicum Strain Tab4ct, A Parasite Of A Horse Fly, Haematopota Sp. (Diptera: Tabanidae)., Robert E. Davis, Jonathan Shao, Yan Zhao, Gail E. Gasparich, Brady J. Gaynor, Nicole Donofrio

Gail Gasparich

Complete Genome Sequence Of Spiroplasma Kunkelii Strain Cr2-3x, Causal Agent Of Corn Stunt Disease In Zea Mays L., Robert E. Davis, Jonathan Shao, Ellen L. Dally, Yan Zhao, Gail E. Gasparich, Brady J. Gaynor, John C. Athey, Nigel A. Harrison, Nicole Donofrio

Gail Gasparich

Satpdb: A Database Of Structurally Annotated Therapeutic Peptides, Sandeep Singh

Sandeep Singh

SATPdb (http://crdd.osdd.net/raghava/satpdb/) is a database of structurally annotated therapeutic peptides, curated from 22 public domain peptide databases/datasets including 9 of our own. The current version holds 19192 unique experimentally validated therapeutic peptide sequences having length between 2 and 50 amino acids. It covers peptides having natural, non-natural and modified residues. These peptides were systematically grouped into 10 categories based on their major function or therapeutic property like 1099 anticancer, 10585 antimicrobial, 1642 drug delivery and 1698 antihypertensive peptides. We assigned or annotated structure of these therapeutic peptides using structural databases (Protein Data Bank) and state-of-the-art structure prediction methods like I-TASSER, …

An Efficient And Sensitive Method For Preparing Cdna Libraries From Scarce Biological Samples, Catherine H. Sterling, Isana Veksler-Lublinsky, Victor R. Ambros

Victor R. Ambros

The preparation and high-throughput sequencing of cDNA libraries from samples of small RNA is a powerful tool to quantify known small RNAs (such as microRNAs) and to discover novel RNA species. Interest in identifying the small RNA repertoire present in tissues and in biofluids has grown substantially with the findings that small RNAs can serve as indicators of biological conditions and disease states. Here we describe a novel and straightforward method to clone cDNA libraries from small quantities of input RNA. This method permits the generation of cDNA libraries from sub-picogram quantities of RNA robustly, efficiently and reproducibly. We demonstrate …

Found And Lost: The Fates Of Horizontally Acquired Genes In Arthropod-Symbiotic Spiroplasma, Wen-Sui Lo, Gail E. Gasparich, Chih-Horng Kuo

Gail Gasparich

Improving The Computer Science In Bioinformatics Through Open Source Pedagogy, John David N. Dionisio, Kam D. Dahlquist

John David N. Dionisio

Bioinformatics relies more than ever on information technologies. This pressures scientists to keep up with software development best practices. However, traditional computer science curricula do not necessarily expose students to collaborative and long-lived software development. Using open source principles, practices, and tools forms an effective pedagogy for software development best practices. This paper reports on a bioinformatics teaching framework implemented through courses introducing computer science students to the field. The courses led to an initial product release consisting of software and an Escherichia coli K12 GenMAPP Gene Database, within a total "incubation time" of six months.

Constructos Teóricos En Economía Común Informática, Rodrigo Lopez-Pablos

Lopez-Pablos, Rodrigo

Repasando elementos de economía comunitaria, solidaría y de la información, se construyen abstracciones teóricas fundamentales en una proto-explicación del rol de la información y el tiempo en la explicación del hecho económico digital y convencional. Infoagregadamente, se sitúa a la emisión informacional como expresión ontológica micro y macroinformática individual y colectiva del ser: el aseguramiento de la infodiversidad civilizatoria generacional; luego, se argumenta sobre la falacia filosófica computacional cognoscitiva detrás de una presunción teórica conceptual equivocada en el estudio y aplicación de lógicas artificiales: su potencial real para la generación de conocimiento híbrido y la creación de conocimiento sin precedentes …

Bayesmotif: De Novo Protein Sorting Motif Discovery From Impure Datasets, Jianjun Hu, F. Zhang

Jianjun Hu

Background

Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms.

Methods

We formulated the protein sorting motif discovery problem as a classification problem …

Hemo: A Sustainable Multi-Objective Evolutionary Optimization Framework, Jianjun Hu, K. Seo, Z. Fan, R. Rosenberg, E. Goodman

Jianjun Hu

No abstract provided.

Improving Protein Localization Prediction Using Amino Acid Group Based Physichemical Encoding, Jianjun Hu, F. Zhang

Jianjun Hu

No abstract provided.

Hemebind: A Novel Method For Heme Binding Residue Prediction By Combining Structural And Sequence Information, R. Liu, Jianjun Hu

Jianjun Hu

Background Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues. Results Here …

Proteomic Characterization Of Her-2/Neu-Overexpressing Breast Cancer Cells, Hexin Chen, G. Pimienta, Y. Gu, X. Sun, Jianjun Hu, M.-S. Kim, R. Chaerkady, M. Gucek, R. Cole, S. Sukumar, A. Pandey

Jianjun Hu

No abstract provided.

Dnabind: A Hybrid Algorithm For Structure-Based Prediction Of Dna-Binding Residues By Combining Machine Learning- And Template-Based Approaches, R. Liu, Jianjun Hu

Jianjun Hu

No abstract provided.

Computational Identification Of Post-Translational Modification-Based Nuclear Import Regulations By Characterizing Nuclear Localization Signal-Import Receptor Interaction, J.-R. Lin, Z. Liu, Jianjun Hu

Jianjun Hu

No abstract provided.

Subcellular Localization Of Marine Bacterial Alkaline Phosphatases, H. Luo, Ronald Benner, R. Long, Jianjun Hu

Jianjun Hu

Bacterial alkaline phosphatases (APases) are important enzymes in organophosphate utilization in the ocean. The subcellular localization of APases has significant ecological implications for marine biota but is largely unknown. The extensive metagenomic sequence databases from the Global Ocean Sampling Expedition provide an opportunity to address this question. A bioinformatics pipeline was developed to identify marine bacterial APases from the metagenomic databases, and a consensus classification algorithm was designed to predict their subcellular localizations. We identified 3,733 bacterial APase sequences (including PhoA, PhoD, and PhoX) and found that cytoplasmic (41%) and extracellular (30%) APases exceed their periplasmic (17%), outer membrane (12%), …

Integrative Disease Classification Based On Cross-Platform Microarray Data, C.-C. Liu, Jianjun Hu, M. Kalakrishnan, H. Huang, X. Zhou

Jianjun Hu

Background Disease classification has been an important application of microarray technology. However, most microarray-based classifiers can only handle data generated within the same study, since microarray data generated by different laboratories or with different platforms can not be compared directly due to systematic variations. This issue has severely limited the practical use of microarray-based disease classification. Results In this study, we tested the feasibility of disease classification by integrating the large amount of heterogeneous microarray datasets from the public microarray repositories. Cross-platform data compatibility is created by deriving expression log-rank ratios within datasets. One may then compare vectors of log-rank …

Scored Protein-Protein Interaction To Predict Subcellular Localizations For Yeast Using Diffusion Kernel, A. Mondal, Jianjun Hu

Jianjun Hu

No abstract provided.

Minimalist Ensemble Algorithms For Genome-Wide Protein Localization Prediction, J.-R. Lin, A. Mondal, R. Liu, Jianjun Hu

Jianjun Hu

Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature …

Limitations And Potentials Of Current Motif Discovery Algorithms, Jianjun Hu, Bin Li, D. Kihara

Jianjun Hu

Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmarked five modern sequence-based motif discovery algorithms using large datasets generated from Escherichia coli RegulonDB. Factors that affect the prediction accuracy, scalability and reliability are characterized. It is revealed that the nucleotide and the binding site level accuracy are very low, while the motif level accuracy …

Seqnls: Nuclear Localization Signal Prediction Based On Frequent Pattern Mining And Linear Motif Scoring, J.-R. Lin, Jianjun Hu

Jianjun Hu

Nuclear localization signals (NLSs) are stretches of residues in proteins mediating their importing into the nucleus. NLSs are known to have diverse patterns, of which only a limited number are covered by currently known NLS motifs. Here we propose a sequential pattern mining algorithm SeqNLS to effectively identify potential NLS patterns without being constrained by the limitation of current knowledge of NLSs. The extracted frequent sequential patterns are used to predict NLS candidates which are then filtered by a linear motif-scoring scheme based on predicted sequence disorder and by the relatively local conservation (IRLC) based masking. The experiment results on …

Integrative Missing Value Estimation For Microarray Data, Jianjun Hu, H. Li, M. Waterman, X. Zhou

Jianjun Hu

Background Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. Results We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets …

Robust And Efficient Genetic Algorithms With Hierarchical Niching And A Sustainable Evolutionary Computation Model, Jianjun Hu, E. Goodman

Jianjun Hu

No abstract provided.

Emd: An Ensemble Algorithm For Discovering Regulatory Motifs In Dna Sequences, Jianjun Hu, Y. Yang, D. Kihara

Jianjun Hu

Background Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms. Results We proposed a novel clustering-based ensemble algorithm named EMD for de novo motif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is …

Computational Prediction Of Heme-Binding Residues By Exploiting Residue Interaction Network, R. Liu, Jianjun Hu

Jianjun Hu

Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based …

Prediction Of Discontinuous B-Cell Epitopes Using Logistic Regression And Structural Information, R. Liu, Jianjun Hu

Jianjun Hu

Computational prediction of discontinuous B-cell epitopes remains challenging, but it is an important task in vaccine design. In this study, we developed a novel computational method to predict discontinuous epitope residues by combining the logistic regression model with two important structural features, B-factor and relative accessible surface area (RASA). We conducted five-fold cross-validation on a representative dataset composed of antigen structures bound with antibodies and independent testing on Epitome database, respectively. Experimental results indicate that besides the well-known RASA feature, B-factor can also be used to identify discontinuous epitopes. Furthermore, these two features are complementary and their combination can remarkably …

Plasq: A Generalized Linear Model-Based Procedure To Determine Allelic Dosage Ini Cancer Cells From Snp Array Data, Thomas Laframboise, David P. Harrington, Barbara A. Weir

David E. Harrington

No abstract provided.

Library Support For Biomedical Research In The Omics Era: 2014- 2015 Report, Rolando Garcia-Milian

Rolando Garcia-Milian

The decreased cost of high-throughput technologies has enabled its use as the main research methods to study biological processes and disorders. In order to understand the relevance of the data generated by these methods, the researcher needs mining and integrating the enormous amount of biomedical information and knowledge contained in the text of the scientific literature and biomedical databases. Accordingly, the ability to access and examine molecular data should not be restricted to bioinformaticians or those with exceptional computer skills. In May 2014, the Cushing/Whitney Medical Library began to provide end-user bioinformatics support to the biomedical researchers of the Yale …

Identification Of Ctla2a, Defb29, Wfdc15b, Serpina1f And Mup19 As Novel Tissue-Specific Secretory Factors In Mouse..Pdf, Jibin Zhang, Jinsoo Ahn, Yeunsu Suh, Seongsoo Hwang, Michael E. Davis, Kichoon Lee

Jibin Zhang