Physical Sciences and Mathematics Commons^™

Characterization Of Landfill Leachate For Enhanced Metal Recovery, Hanna Fulford, Amisha Shah, Inez Hua, Nadezhda Zyaykina, Lori Hoagland, Alejandro Rodriguez Sanchez, Umut Bicim

Discovery Undergraduate Interdisciplinary Research Internship

Landfills contain a trove of valuable materials, such as critical, precious, and rare earth metals, that are integral to the United State’s economy and national security. The leachate that filters through landfills picks up these materials, which allows for the possibility of recovery. For this research, samples will be analyzed from landfills throughout the Midwestern United States to provide a baseline on water quality constituents, elements present, and microbial activity. Preliminary data for this study was acquired by analyzing samples of landfill leachate from a landfill in northern Indiana. pH readings indicate that the leachate is slightly basic. It also …

Characterization Of Microbial Populations In Landfill Leachate, Umut M. Bicim, Hanna Fulford, Lori A. Hoagland, Alejandro R. Sanchez, Amisha D. Shah, Inez Hua

Discovery Undergraduate Interdisciplinary Research Internship

In the United States, municipal solid waste (MSW) landfills remain a potential mining source of recoverable materials, including but not limited to critical, precious, and rare earth metals found in electronic waste. This is possible due to collectible leachate that filters through MSW landfills, carrying metals, nutrients of value, and microbes—some of which may hold key metal bioleaching properties—within. The purpose of this study is to begin analyzing leachate from MSW landfills in the American Midwest to understand the composition of microbial communities within these landfills. Landfill leachate samples sourced in northern Indiana, representing the landfill process during unique times …

Prediction Of Local Quality Of Protein Structure Models Considering Spatial Neighbors In Graphical Models., Woong Hee Shin, Xuejiao Kang, Jian Zhang, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Protein tertiary structure prediction methods have matured in recent years. However, some proteins defy accurate prediction due to factors such as inadequate template structures. While existing model quality assessment methods predict global model quality relatively well, there is substantial room for improvement in local quality assessment, i.e. assessment of the error at each residue position in a model. Local quality is a very important information for practical applications of structure models such as interpreting/designing site-directed mutagenesis of proteins. We have developed a novel local quality assessment method for protein tertiary structure models. The method, named Graph-based Model Quality assessment method …

Missing Gene Identification Using Functional Coherence Scores, Meghana Chitale, Ishita K. Khan, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Reconstructing metabolic and signaling pathways is an effective way of interpreting a genome sequence. A challenge in a pathway reconstruction is that often genes in a pathway cannot be easily found, reflecting current imperfect information of the target organism. In this work, we developed a new method for finding missing genes, which integrates multiple features, including gene expression, phylogenetic profile, and function association scores. Particularly, for considering function association between candidate genes and neighboring proteins to the target missing gene in the network, we used Co-occurrence Association Score (CAS) and PubMed Association Score (PAS), which are designed for capturing functional …

On The Origin Of Protein Superfamilies And Superfolds, Abram Magner, Wojciech Szpankowski, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are …

Protein-Protein Docking Using Region-Based 3d Zernike Descriptors., Vishwesh Venkatraman, Yifeng D. Yang, Lee Sael, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Background

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur.

Results

We present a novel protein docking algorithm based …

Application Of 3d Zernike Descriptors To Shape-Based Ligand Similarity Searching, Vishwesh Venkatraman, Padmasini Ramji Chakravarthy, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Background

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed.

Results

In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, …

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

Department of Biological Sciences Faculty Publications

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 …