Browsing by Author "Department of BioHealth Informatics, School of Informatics and Computing"
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Item Comparative and temporal transcriptome analysis of peste des petits ruminants virus infected goat peripheral blood mononuclear cells(Elsevier, 2017-02) Manjunath, Siddappa; Mishra, Bishnu Prasad; Mishra, Bina; Sahoo, Aditya Prasad; Tiwari, Ashok K.; Rajak, Kaushal Kishore; Muthuchelvan, D.; Saxena, Shikha; Santra, Lakshman; Sahu, Amit Ranjan; Wani, Sajad Ahmad; Singh, R. P.; Singh, Y. P.; Pandey, Aruna; Kanchan, Sonam; Singh, R. K.; Kumar, Gandham Ravi; Janga, Sarath Chandra; Department of BioHealth Informatics, School of Informatics and ComputingPeste des petits ruminanats virus (PPRV), a morbillivirus causes an acute, highly contagious disease – peste des petits ruminants (PPR), affecting goats and sheep. Sungri/96 vaccine strain is widely used for mass vaccination programs in India against PPR and is considered the most potent vaccine providing long-term immunity. However, occurrence of outbreaks due to emerging PPR viruses may be a challenge. In this study, the temporal dynamics of immune response in goat peripheral blood mononuclear cells (PBMCs) infected with Sungri/96 vaccine virus was investigated by transcriptome analysis. Infected goat PBMCs at 48 h and 120 h post infection revealed 2540 and 2000 differentially expressed genes (DEGs), respectively, on comparison with respective controls. Comparison of the infected samples revealed 1416 DEGs to be altered across time points. Functional analysis of DEGs reflected enrichment of TLR signaling pathways, innate immune response, inflammatory response, positive regulation of signal transduction and cytokine production. The upregulation of innate immune genes during early phase (between 2-5 days) viz. interferon regulatory factors (IRFs), tripartite motifs (TRIM) and several interferon stimulated genes (ISGs) in infected PBMCs and interactome analysis indicated induction of broad-spectrum anti-viral state. Several Transcription factors – IRF3, FOXO3 and SP1 that govern immune regulatory pathways were identified to co-regulate the DEGs. The results from this study, highlighted the involvement of both innate and adaptive immune systems with the enrichment of complement cascade observed at 120 h p.i., suggestive of a link between innate and adaptive immune response. Based on the transcriptome analysis and qRT-PCR validation, an in vitro mechanism for the induction of ISGs by IRFs in an interferon independent manner to trigger a robust immune response was predicted in PPRV infection.Item Differential miRNA Expression in Cells and Matrix Vesicles in Vascular Smooth Muscle Cells from Rats with Kidney Disease(PLOS, 2015-06-26) Chaturvedi, Praneet; Chen, Neal X.; O’Neill, Kalisha; McClintick, Jeanette N.; Moe, Sharon M.; Janga, Sarath Chandra; Department of BioHealth Informatics, School of Informatics and ComputingVascular calcification is a complex process and has been associated with aging, diabetes, chronic kidney disease (CKD). Although there have been several studies that examine the role of miRNAs (miRs) in bone osteogenesis, little is known about the role of miRs in vascular calcification and their role in the pathogenesis of vascular abnormalities. Matrix vesicles (MV) are known to play in important role in initiating vascular smooth muscle cell (VSMC) calcification. In the present study, we performed miRNA microarray analysis to identify the dysregulated miRs between MV and VSMC derived from CKD rats to understand the role of post-transcriptional regulatory networks governed by these miRNAs in vascular calcification and to uncover the differential miRNA content of MV. The percentage of miRNA to total RNA was increased in MV compared to VSMC. Comparison of expression profiles of miRNA by microarray demonstrated 33 miRs to be differentially expressed with the majority (~ 57%) of them down-regulated. Target genes controlled by differentially expressed miRNAs were identified utilizing two different complementary computational approaches Miranda and Targetscan to understand the functions and pathways that may be affected due to the production of MV from calcifying VSMC thereby contributing to the regulation of genes by miRs. We found several processes including vascular smooth muscle contraction, response to hypoxia and regulation of muscle cell differentiation to be enriched. Signaling pathways identified included MAP-kinase and wnt signaling that have previously been shown to be important in vascular calcification. In conclusion, our results demonstrate that miRs are concentrated in MV from calcifying VSMC, and that important functions and pathways are affected by the miRs dysregulation between calcifying VSMC and the MV they produce. This suggests that miRs may play a very important regulatory role in vascular calcification in CKD by controlling an extensive network of post-transcriptional targets.Item Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks(Nature Publishing Group, 2016-05-10) Nishtala, Sneha; Neelamraju, Yaseswini; Janga, Sarath Chandra; Department of BioHealth Informatics, School of Informatics and ComputingRNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networksItem Dual-Gated Volumetric Modulated Arc Therapy(Springer (Biomed Central Ltd.), 2014) Fahimian, Benjamin; Wu, Junqing; Wu, Huanmei; Geneser, Sarah; Xing, Lei; Department of BioHealth Informatics, School of Informatics and ComputingBACKGROUND: Gated Volumetric Modulated Arc Therapy (VMAT) is an emerging radiation therapy modality for treatment of tumors affected by respiratory motion. However, gating significantly prolongs the treatment time, as delivery is only activated during a single respiratory phase. To enhance the efficiency of gated VMAT delivery, a novel dual-gated VMAT (DG-VMAT) technique, in which delivery is executed at both exhale and inhale phases in a given arc rotation, is developed and experimentally evaluated. METHODS: Arc delivery at two phases is realized by sequentially interleaving control points consisting of MUs, MLC sequences, and angles of VMAT plans generated at the exhale and inhale phases. Dual-gated delivery is initiated when a respiration gating signal enters the exhale window; when the exhale delivery concludes, the beam turns off and the gantry rolls back to the starting position for the inhale window. The process is then repeated until both inhale and exhale arcs are fully delivered. DG-VMAT plan delivery accuracy was assessed using a pinpoint chamber and diode array phantom undergoing programmed motion. RESULTS: DG-VMAT delivery was experimentally implemented through custom XML scripting in Varian's TrueBeam™ STx Developer Mode. Relative to single gated delivery at exhale, the treatment time was improved by 95.5% for a sinusoidal breathing pattern. The pinpoint chamber dose measurement agreed with the calculated dose within 0.7%. For the DG-VMAT delivery, 97.5% of the diode array measurements passed the 3%/3 mm gamma criterion. CONCLUSIONS: The feasibility of DG-VMAT delivery scheme has been experimentally demonstrated for the first time. By leveraging the stability and natural pauses that occur at end-inspiration and end-exhalation, DG-VMAT provides a practical method for enhancing gated delivery efficiency by up to a factor of two.Item An efficient algorithm for the blocked pattern matching problem(Oxford, 2015-10) Deng, Fei; Wang, Lusheng; Liu, Xiaowen; Department of BioHealth Informatics, School of Informatics and ComputingMotivation: Tandem mass spectrometry (MS) has become the method of choice for protein identification and quantification. In the era of big data biology, tandem mass spectra are often searched against huge protein databases generated from genomes or RNA-Seq data for peptide identification. However, most existing tools for MS-based peptide identification compare a tandem mass spectrum against all peptides in a database whose molecular masses are similar to the precursor mass of the spectrum, making mass spectral data analysis slow for huge databases. Tag-based methods extract peptide sequence tags from a tandem mass spectrum and use them as a filter to reduce the number of candidate peptides, thus speeding up the database search. Recently, gapped tags have been introduced into mass spectral data analysis because they improve the sensitivity of peptide identification compared with sequence tags. However, the blocked pattern matching (BPM) problem, which is an essential step in gapped tag-based peptide identification, has not been fully solved. Results: In this article, we propose a fast and memory-efficient algorithm for the BPM problem. Experiments on both simulated and real datasets showed that the proposed algorithm achieved high speed and high sensitivity for peptide filtration in peptide identification by database search.Item Evaluating Methods for Identifying Cancer in Free-Text Pathology Reports Using Various Machine Learning and Data Preprocessing Approaches(IOS, 2015) Kasthurirathne, Suranga Nath; Dixon, Brian E.; Grannis, Shaun J.; Department of BioHealth Informatics, School of Informatics and ComputingAutomated detection methods can address delays and incompleteness in cancer case reporting. Existing automated efforts are largely dependent on complex dictionaries and coded data. Using a gold standard of manually reviewed pathology reports, we evaluated the performance of alternative input formats and decision models on a convenience sample of free-text pathology reports. Results showed that the input format significantly impacted performance, and specific algorithms yielded better results for presicion, recall and accuracy. We conclude that our approach is sufficiently accurate for practical purposes and represents a generalized process.Item Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease(2015) Yan, Jingwen; Kim, Sungeun; Nho, Kwangsik; Chen, Rui; Risacher, Shannon L.; Moore, Jason H.; Saykin, Andrew J.; Shen, Li; Department of BioHealth Informatics, School of Informatics and ComputingAs the most common type of dementia, Alzheimer's disease (AD) is a neurodegenerative disorder initially manifested by impaired memory performances. While the diagnosis information indicates a dichotomous status of a patient, memory scores have the potential to capture the continuous nature of the disease progression and may provide more insights into the underlying mechanism. In this work, we performed a targeted genetic study of memory scores on an AD cohort to identify the associations between a set of genes highly expressed in the hippocampal region and seven cognitive scores related to episodic memory. Both main effects and interaction effects of the targeted genetic markers on these correlated memory scores were examined. In addition to well-known AD genetic markers APOE and TOMM40, our analysis identified a new risk gene NAV2 through the gene-level main effect analysis. NAV2 was found to be significantly and consistently associated with all seven episodic memory scores. Genetic interaction analysis also yielded a few promising hits warranting further investigation, especially for the RAVLT list B Score.Item The human RBPome: From genes and proteins to human disease(Elsevier, 2015-09) Neelamraju, Yaseswini; Hashemikhabir, Seyedsasan; Janga, Sarath Chandra; Department of BioHealth Informatics, School of Informatics and ComputingRNA binding proteins (RBPs) play a central role in mediating post transcriptional regulation of genes. However less is understood about them and their regulatory mechanisms. In this study, we construct a catalogue of 1344 experimentally confirmed RBPs. The domain architecture of RBPs enabled us to classify them into three groups — Classical (29%), Non-classical (19%) and unclassified (52%). A higher percentage of proteins with unclassified domains reveals the presence of various uncharacterised motifs that can potentially bind RNA. RBPs were found to be highly disordered compared to Non-RBPs (p < 2.2e-16, Fisher's exact test), suggestive of a dynamic regulatory role of RBPs in cellular signalling and homeostasis. Evolutionary analysis in 62 different species showed that RBPs are highly conserved compared to Non-RBPs (p < 2.2e-16, Wilcox-test), reflecting the conservation of various biological processes like mRNA splicing and ribosome biogenesis. The expression patterns of RBPs from human proteome map revealed that ~ 40% of them are ubiquitously expressed and ~ 60% are tissue-specific. RBPs were also seen to be highly associated with several neurological disorders, cancer and inflammatory diseases. Anatomical contexts like B cells, T-cells, foetal liver and foetal brain were found to be strongly enriched for RBPs, implying a prominent role of RBPs in immune responses and different developmental stages. The catalogue and meta-analysis presented here should form a foundation for furthering our understanding of RBPs and the cellular networks they control, in years to come. This article is part of a Special Issue entitled: Proteomics in India.Item Identification of Patients with Family History of Pancreatic Cancer - Investigation of an NLP System Portability(IOS, 2015) Mehrabi, Saeed; Krishnan, Anand; Roch, Alexandra M.; Schmidt, Heidi; Li, DingCheng; Kesterson, Joe; Beesley, Chris; Dexter, Paul; Schmidt, Max; Palakal, Mathew; Liu, Hongfang; Department of BioHealth Informatics, School of Informatics and ComputingIn this study we have developed a rule-based natural language processing (NLP) system to identify patients with family history of pancreatic cancer. The algorithm was developed in a Unstructured Information Management Architecture (UIMA) framework and consisted of section segmentation, relation discovery, and negation detection. The system was evaluated on data from two institutions. The family history identification precision was consistent across the institutions shifting from 88.9% on Indiana University (IU) dataset to 87.8% on Mayo Clinic dataset. Customizing the algorithm on the the Mayo Clinic data, increased its precision to 88.1%. The family member relation discovery achieved precision, recall, and F-measure of 75.3%, 91.6% and 82.6% respectively. Negation detection resulted in precision of 99.1%. The results show that rule-based NLP approaches for specific information extraction tasks are portable across institutions; however customization of the algorithm on the new dataset improves its performance.Item The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature(JMIR, 2016) Sawesi, Suhila; Rashrash, Mohamed; Phalakornkule, Kanitha; Carpenter, Janet S.; Jones, Josette F.; Department of BioHealth Informatics, School of Informatics and ComputingBackground: Advancements in information technology (IT) and its increasingly ubiquitous nature expand the ability to engage patients in the health care process and motivate health behavior change. Objective: Our aim was to systematically review the (1) impact of IT platforms used to promote patients' engagement and to effect change in health behaviors and health outcomes, (2) behavior theories or models applied as bases for developing these interventions and their impact on health outcomes, (3) different ways of measuring health outcomes, (4) usability, feasibility, and acceptability of these technologies among patients, and (5) challenges and research directions for implementing IT platforms to meaningfully impact patient engagement and health outcomes. Methods: PubMed, Web of Science, PsycINFO, and Google Scholar were searched for studies published from 2000 to December 2014. Two reviewers assessed the quality of the included papers, and potentially relevant studies were retrieved and assessed for eligibility based on predetermined inclusion criteria. Results: A total of 170 articles met the inclusion criteria and were reviewed in detail. Overall, 88.8% (151/170) of studies showed positive impact on patient behavior and 82.9% (141/170) reported high levels of improvement in patient engagement. Only 47.1% (80/170) referenced specific behavior theories and only 33.5% (57/170) assessed the usability of IT platforms. The majority of studies used indirect ways to measure health outcomes (65.9%, 112/170). Conclusions: In general, the review has shown that IT platforms can enhance patient engagement and improve health outcomes. Few studies addressed usability of these interventions, and the reason for not using specific behavior theories remains unclear. Further research is needed to clarify these important questions. In addition, an assessment of these types of interventions should be conducted based on a common framework using a large variety of measurements; these measurements should include those related to motivation for health behavior change, long-standing adherence, expenditure, satisfaction, and health outcomes. [JMIR Med Inform 2016;4(1):e1]