Bioinformatics Commons^™

Gene-Based Clustering Algorithms: Comparison Between Denclue, Fuzzy-C, And Birch, Martin C. Nwadiugwu

Interdisciplinary Informatics Faculty Publications

The current study seeks to compare 3 clustering algorithms that can be used in gene-based bioinformatics research to understand disease networks, protein-protein interaction networks, and gene expression data. Denclue, Fuzzy-C, and Balanced Iterative and Clustering using Hierarchies (BIRCH) were the 3 gene-based clustering algorithms selected. These algorithms were explored in relation to the subfield of bioinformatics that analyzes omics data, which include but are not limited to genomics, proteomics, metagenomics, transcriptomics, and metabolomics data. The objective was to compare the efficacy of the 3 algorithms and determine their strength and drawbacks. Result of the review showed that unlike Denclue and …

Trimethyltin-Induced Cerebellar Damage On Adult Male Wistar Rats. Trimetil Estaño Induce Daño Cerebral En Ratas Machos Adultas Wistar., M. S. Ajao, A. Okesina, Martin C. Nwadiugwu

Interdisciplinary Informatics Faculty Publications

Abstract: This research work was done to investigate the acute toxicological effect of trimethyltin chloride on the cerebellum of Wistar rat. Ten adult male Wistar rats were used for the study. The animals were grouped into two: Group A and B, with five adult male Wistar rats in each group. Group A serves as the trimethyltin (TMT) group, while group B serves as the normal saline (NS) group. 3mg/kg of trimethyltin chloride was administered to animals in the TMT group, while 1.0mls of normal saline was administered to the animals in the NS group via intraperitoneal route for 3 …

Genome-Wide Detection And Analysis Of Multifunctional Genes, Yuri Pritykin, Dario Ghersi, Mona Singh

Interdisciplinary Informatics Faculty Publications

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, …

Molblocks: Decomposing Small Molecule Sets And Uncovering Enriched Fragments, Dario Ghersi, Mona Singh

Interdisciplinary Informatics Faculty Publications

The chemical structures of biomolecules, whether naturally occurring or synthetic, are composed of functionally important building blocks. Given a set of small molecules—for example, those known to bind a particular protein—computationally decomposing them into chemically meaningful fragments can help elucidate their functional properties, and may be useful for designing novel compounds with similar properties. Here we introduce molBLOCKS, a suite of programs for breaking down sets of small molecules into fragments according to a predefined set of chemical rules, clustering the resulting fragments, and uncovering statistically enriched fragments. Among other applications, our software should be a great aid in large-scale …

Identifying Aging-Related Genes In Mouse Hippocampus Using Gateway Nodes, Kathryn Dempsey Cooper, Hesham Ali

Interdisciplinary Informatics Faculty Publications

Background: High-throughput studies continue to produce volumes of metadata representing valuable sources of information to better guide biological research. With a stronger focus on data generation, analysis models that can readily identify actual signals have not received the same level of attention. This is due in part to high levels of noise and data heterogeneity, along with a lack of sophisticated algorithms for mining useful information. Networks have emerged as a powerful tool for modeling high-throughput data because they are capable of representing not only individual biological elements but also different types of relationships en masse. Moreover, well-established graph …

Interaction-Based Discovery Of Functionally Important Genes In Cancers, Dario Ghersi, Mona Singh

Interdisciplinary Informatics Faculty Publications

A major challenge in cancer genomics is uncovering genes with an active role in tumorigenesis from a potentially large pool of mutated genes across patient samples. Here we focus on the interactions that proteins make with nucleic acids, small molecules, ions and peptides, and show that residues within proteins that are involved in these interactions are more frequently affected by mutations observed in large-scale cancer genomic data than are other residues. We leverage this observation to predict genes that play a functionally important role in cancers by introducing a computational pipeline (http://canbind.princeton.edu) for mapping large-scale cancer exome data …

A Parallel Template For Implementing Filters For Biological Correlation Networks, Kathryn Dempsey Cooper, Vladimir Ufimtsev, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Publications

High throughput biological experiments are critical for their role in systems biology – the ability to survey the state of cellular mechanisms on the broad scale opens possibilities for the scientific researcher to understand how multiple components come together, and what goes wrong in disease states. However, the data returned from these experiments is massive and heterogeneous, and requires intuitive and clever computational algorithms for analysis. The correlation network model has been proposed as a tool for modeling and analysis of this high throughput data; structures within the model identified by graph theory have been found to represent key players …

Automated Identification Of Binding Sites Forphosphorylated Ligands In Protein Structures, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

Phosphorylation is a crucial step in many cellular processes, ranging from metabolic reactions involved in energy transformation to signaling cascades. In many instances, protein domains specifically recognize the phosphogroup. Knowledge of the binding site provides insights into the interaction, and it can also be exploited for therapeutic purposes. Previous studies have shown that proteins interacting with phosphogroups are highly heterogeneous, and no single property can be used to reliably identify the binding site. Here we present an energy-based computational procedure that exploits the protein three-dimensional structure to identify binding sites involved in the recognition of phosphogroups. The procedure is validated …

Beyond Structural Genomics: Computational Approaches For The Identification Of Ligand Binding Sites In Protein Structures, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

t Structural genomics projects have revealed structures for a large number of proteins of unknown function. Understanding the interactions between these proteins and their ligands would provide an initial step in their functional characterization. Binding site identification methods are a fast and cost-effective way to facilitate the characterization of functionally important protein regions. In this review we describe our recently developed methods for binding site identification in the context of existing methods. The advantage of energy-based approaches is emphasized, since they provide flexibility in the identifi- cation and characterization of different types of binding sites

Systematic Assessment Of Accuracy Of Comparative Model Of Proteins Belonging To Different Structural Fold Classes, Subrata Chakrabarty, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

In the absence of experimental structures, comparative modeling continues to be the chosen method for retrieving structural information on target proteins. However, models lack the accuracy of experimental structures. Alignment error and structural divergence (between target and template) influence model accuracy the most. Here, we examine the potential additional impact of backbone geometry, as our previous studies have suggested that the structural class (all-α, αβ, all-β) of a protein may influence the accuracy of its model. In the twilight zone (sequence identity ≤ 30%) and at a similar level of target-template divergence, the accuracy of protein models does indeed follow …

Computer Simulations Of Heterologous Immunity: Highlights Of An Interdisciplinary Cooperation, Claudia Calcagno, Roberto Puzone, Yanthe E. Pearson, Yiming Cheng, Dario Ghersi, Liisa K. Selin, Raymond M. Welsh, Franco Celada

Interdisciplinary Informatics Faculty Publications

The relationship between biological research and mathematical modeling is complex, critical, and vital. In this review, we summarize the results of the collaboration between two laboratories, exploring the interaction between mathematical modeling and wet-lab immunology. During this collaboration several aspects of the immune defence against viral infections were investigated, focusing primarily on the subject of heterologous immunity. In this manuscript, we emphasize the topics where computational simulations were applied in conjunction with experiments, such as immune attrition, the growing and shrinking of cross-reactive T cell repertoires following repeated infections, the short and long-term effects of cross-reactive immunological memory, and the …

A Parallel Graph Sampling Algorithm For Analyzing Gene Correlation Networks, Kathryn Dempsey Cooper, Kanimathi Duraisamy, Hesham Ali, Sanjukta Bhowmick

Interdisciplinary Informatics Faculty Publications

Effcient analysis of complex networks is often a challenging task due to its large size and the noise inherent in the system. One popular method of overcoming this problem is through graph sampling, that is extracting a representative subgraph from the larger network. The accuracy of the sample is validated by comparing the combinatorial properties of the subgraph and the original network. However, there has been little study in comparing networks based on the applications that they represent. Furthermore, sampling methods are generally applied agnostically, without mapping to the requirements of the underlying analysis. In this paper,we introduce a parallel …

Biochemical Profiling Of Histone Binding Selectivity Of The Yeast Bromodomain Family, Qiang Zhang, Suvobrata Chakravarty, Dario Ghersi, Lei Zeng, Alexander N. Plotnikov, Roberto Sanchez, Ming-Ming Zhou

Interdisciplinary Informatics Faculty Publications

Background: It has been shown that molecular interactions between site-specific chemical modifications such as acetylation and methylation on DNA-packing histones and conserved structural modules present in transcriptional proteins are closely associated with chromatin structural changes and gene activation. Unlike methyl-lysine that can interact with different protein modules including chromodomains, Tudor and MBT domains, as well as PHD fingers, acetyl-lysine (Kac) is known thus far to be recognized only by bromodomains. While histone lysine acetylation plays a crucial role in regulation of chromatin-mediated gene transcription, a high degree of sequence variation of the acetyl-lysine binding site in the bromodomains has …

Easymifs And Sitehound: A Toolkit For The Identification Of Ligand-Binding Sites In Protein Structures, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

Summary: SITEHOUND uses Molecular Interaction Fields (MIFs) produced by EASYMIFS to identify protein structure regions that show a high propensity for interaction with ligands. The type of binding site identified depends on the probe atom used in the MIF calculation. The input to EASYMIFS is a PDB file of a protein structure; the output MIF serves as input to SITEHOUND, which in turn produces a list of putative binding sites. Extensive testing of SITEHOUND for the detection of binding sites for drug-like molecules and phosphorylated ligands has been carried out.

Availability: EASYMIFS and SITEHOUND executables for Linux, Mac …

Sitehound-Web: A Server For Ligand Binding Site Identification In Protein Structures, Marylens Hernandez, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

SITEHOUND-web (http://sitehound.sanchezlab.org) is a binding-site identification server powered by the SITEHOUND program. Given a protein structure in PDB format SITEHOUND-web will identify regions of the protein characterized by favorable interactions with a probe molecule. These regions correspond to putative ligand binding sites. Depending on the probe used in the calculation, sites with preference for different ligands will be identified. Currently, a carbon probe for identification of binding sites for drug-like molecules, and a phosphate probe for phosphorylated ligands (ATP, phoshopeptides, etc.) have been implemented. SITEHOUND-web will display the results in HTML pages including an interactive 3D representation of …

Improving Accuracy And Efficiency Of Blind Protein-Ligand Docking By Focusing On Predicted Binding Sites, Dario Ghersi, Roberto Sanchez

Interdisciplinary Informatics Faculty Publications

The use of predicted binding sites (binding sites calculated from the protein structure alone) is evaluated here as a tool to focus the docking of small molecule ligands into protein structures, simulating cases where the real binding sites are unknown. The resulting approach consists of a few independent docking runs carried out on small boxes, centered on the predicted binding sites, as opposed to one larger blind docking run that covers the complete protein structure. The focused and blind approaches were compared using a set of 77 known protein-ligand complexes and 19 ligand-free structures. The focused approach is shown to: …

Narrowed Tcr Repertoire And Viral Escape As A Consequence Of Heterologous Immunity, Markus Cornberg, Alex T. Chen, Lee A. Wilkinson, Michael A. Brehm, Sung-Kwon Kim, Claudia Calcagno, Dario Ghersi, Roberto Puzone, Franco Celada, Raymond M. Welsh, Liisa K. Selin

Interdisciplinary Informatics Faculty Publications

Why some virus-specific CD8 TCR repertoires are diverse and others restricted or “oligoclonal” has been unknown. We show here that oligoclonality and extreme clonal dominance can be a consequence ofTcell crossreactivity. Lymphocytic choriomeningitis virus (LCMV) and Pichinde virus (PV) encode NP205–212 epitopes that induce different but highly cross-reactive diverseTCRrepertoires. Homologous viral challenge ofimmune mice only slightly skewed the repertoire and enriched for predictable TCR motifs. However, heterologous viral challenge resulted in a narrow oligoclonal repertoire with dominant clones with unpredictableTCRsequences.This shift in clonal dominance varied with the private, i.e., unique, specificity of the host’s TCR repertoire and was simulated using …