Computer Sciences Commons^™

Algorithms And Tools For Computational Analysis Of Human Transcriptome Using Rna-Seq, Nan Deng

Wayne State University Dissertations

Alternative splicing plays a key role in regulating gene expression, and more than 90% of human genes are alternatively spliced through different types of alternative splicing. Dysregulated alternative splicing events have been linked to a number of human diseases. Recently, high-throughput RNA-Seq technologies have provided unprecedented opportunities to better characterize and understand transcriptomes, in particular useful for the detection of splicing variants between healthy and diseased human transcriptomes.

We have developed two novel algorithms and tools and a computational workflow to interrogate human transcriptomes between healthy and diseased conditions. The first is a read count-based Expectation-Maximization (EM) algorithm and tool, …

Information In Biological Systems And The Fluctuation Theorem, Yaşar Demirel

Department of Chemical and Biomolecular Engineering: Faculty Publications

Some critical trends in information theory, its role in living systems and utilization in fluctuation theory are discussed. The mutual information of thermodynamic coupling is incorporated into the generalized fluctuation theorem by using information theory and nonequilibrium thermodynamics. Thermodynamically coupled dissipative structures in living systems are capable of degrading more energy, and processing complex information through developmental and environmental constraints. The generalized fluctuation theorem can quantify the hysteresis observed in the amount of the irreversible work in nonequilibrium regimes in the presence of information and thermodynamic coupling.

Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang

Research outputs 2014 to 2021

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search …

Rigidity Analysis Of Protein Biological Assemblies And Periodic Crystal Structures, Filip Jagodzinski, Pamela Clark, Jessica Grant, Tiffany Liu, Samantha Monastra, Ileana Streinu

All Faculty Scholarship for the College of the Sciences

Background

We initiate in silico rigidity-theoretical studies of biological assemblies and small crystals for protein structures. The goal is to determine if, and how, the interactions among neighboring cells and subchains affect the flexibility of a molecule in its crystallized state. We use experimental X-ray crystallography data from the Protein Data Bank (PDB). The analysis relies on an effcient graph-based algorithm. Computational experiments were performed using new protein rigidity analysis tools available in the new release of our KINARI-Web server http://kinari.cs.umass.edu.

Results

We provide two types of results: on biological assemblies and on crystals. We found that when only isolated …

Automatic Domain Identification For Linked Open Data, Sarasi Lalithsena, Pascal Hitzler, Amit P. Sheth, Prateek Jain

Kno.e.sis Publications

Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose …

Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing …

Pcaanalyser: A 2d-Image Analysis Based Module For Effective Determination Of Prostate Cancer Progression In 3d Culture, Md Tamjidul Hoque, Louisa C. E. Windus, Carrie J. Lovitt, Vicky M. Avery

Computer Science Faculty Publications

Three-dimensional (3D) in vitro cell based assays for Prostate Cancer (PCa) research are rapidly becoming the preferred alternative to that of conventional 2D monolayer cultures. 3D assays more precisely mimic the microenvironment found in vivo, and thus are ideally suited to evaluate compounds and their suitability for progression in the drug discovery pipeline. To achieve the desired high throughput needed for most screening programs, automated quantification of 3D cultures is required. Towards this end, this paper reports on the development of a prototype analysis module for an automated high-content-analysis (HCA) system, which allows for accurate and fast investigation of …

City Notifications As A Data Source For Traffic Management, Pramod Anantharam, Biplav Srivastava

Kno.e.sis Publications

A common problem for cities of developing countries like India in managing traffic is the lack of basic automated instrumentation to track road conditions or vehicle locations. Still, to help their citizens make informed travel decisions based on changing city dynamics; many cities have an authorized, city-initiated, notification service in place to alert subscribing commuters about road conditions. Here, alternative means may be used to create informal textual notifications e.g., inputs from field personnel, citizen updates, and pre-authorized events from city calendar. In this paper, we show that collections of such notifications, when processed with information extraction techniques, can turn …

A Statistical And Schema Independent Approach To Identify Equivalent Properties On Linked Data, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Prateek Jain, Amit P. Sheth, Sanjaya Wijeratne

Kno.e.sis Publications

Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community recently. Currently it consists of approximately 295 interlinked datasets with over 50 billion triples including 500 million links, and continues to expand in size. This vast source of structured information has the potential to have a significant impact on knowledge-based applications. However, a key impediment to the use of LOD cloud is limited support for data integration tasks over concepts, instances, and properties. Efforts to address this limitation over properties have focused on matching data-type properties across datasets; however, matching of object-type properties has not received …

Mining Effective Multi-Segment Sliding Window For Pathogen Incidence Rate Prediction, Lei Duan, Changjie Tang, Xiasong Li, Guozhu Dong, Xianming Wang, Jie Zuo, Min Jiang, Zhongqi Li, Yongqing Zhang

Kno.e.sis Publications

Pathogen incidence rate prediction, which can be considered as time series modeling, is an important task for infectious disease incidence rate prediction and for public health. This paper investigates the application of a genetic computation technique, namely GEP, for pathogen incidence rate prediction. To overcome the shortcomings of traditional sliding windows in GEP-based time series modeling, the paper introduces the problem of mining effective sliding window, for discovering optimal sliding windows for building accurate prediction models. To utilize the periodical characteristic of pathogen incidence rates, a multi-segment sliding window consisting of several segments from different periodical intervals is proposed and …

Types Of Property Pairs And Alignment On Linked Datasets - A Preliminary Analysis, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Dataset publication on the Web has been greatly influenced by the Linked Open Data (LOD) project. Many interlinked datasets have become freely available on the Web creating a structured and distributed knowledge representation. Analysis and aligning of concepts and instances in these interconnected datasets have received a lot of attention in the recent past compared to properties. We identify three different categories of property pairs found in the alignment process and study their relative distribution among well known LOD datasets. We also provide comparative analysis of state-of-the-art techniques with regard to different categories, highlighting their capabilities. This could lead to …

From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton

Kno.e.sis Publications

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and provides intuitive form-based interfaces to facilitate querying of the data, commonly used by the life science researchers that we study. The second approach utilizes a large OWL ontology and the same datasets associated as RDF instances of the ontology. Both approaches are being used in parallel by a team of cell biologists in their daily research activities, with the objective of gradually replacing the conventional approach with the knowledge-driven one. We describe several benefits …

Crisis Response Coordination In Online Communities, Hemant Purohit

Kno.e.sis Publications

During recent crises, citizens (sensors) are increasingly using social media to share variety of information- situation on the ground, emerging needs, donation offers, damage, etc. In such an evolving ad-hoc community, how can we extract actionable nuggets from the social media streams to aid relief efforts? This doctoral consortium presentation summarizes a framework to analyze social data and manage information to assist coordination by focusing on three important questions to answer: Whom to coordinate with, Why to coordinate and How to coordinate, with exemplary insights for needs and availability from the recent disaster events.

Demo: Approximate Semantic Matching In The Collider Event Processing Engine, Souleiman Hasan, Kalpa Gunaratna, Yongrui Qin, Edward Curry

Kno.e.sis Publications

This demo presents a use case from the energy management domain. It builds upon previous work on approximate semantic matching of heterogeneous events and compares two semantic matching scenarios: exact and approximate. It illustrates how a large number of exact matching event subscriptions are needed to match heterogeneous power consumption events. It then demonstrates how a small number of approximate semantic matching subscriptions are needed but possibly with a lower true positives/negatives performance. The demo is delivered via the COLLIDER approximate event processing engine currently under development in DERI.

Genome Wide Search For Pseudo Knotted Non-Coding Rnas, Meghana S. Vasavada

Theses

Non-coding RNAs (ncRNAs) are the functional RNA molecules that are involved in many biological processes including gene regulation, chromosome replication and RNA modification. Searching genomes using computational methods has become an important asset for prediction and annotation of ncRNAs. To annotate an individual genome for a specific family of ncRNAs, a computational tool is interpreted to scan through the genome and align its sequence segments to some structure model for the ncRNA family. With the recent advances in detecting an ncRNA in the genome, heuristic techniques are designed to perform an accurate search and sequence-structure alignment. This study uses a …

A Gpu Program To Compute Snp-Snp Interactions In Genome-Wide Association Studies, Srividya Ramakrishnan

Theses

With the recent advances in the next generation sequencing technologies, short read sequences of human genome are made more accessible. Paired end sequencing of short reads is currently the most sensitive method for detecting somatic mutations that arise during tumor development. In this study, a novel approach to optimize the detection of structural variants using a new short read alignment program is presented.

Pairwise interaction effects of the Single Nucleotide Polymorphisms (SNPs) have proven to uncover the underlying complex disease traits. Computing the disease risk based on the interaction effects of SNPs on a case - control study is a …

Rna-Sequence Analysis Of Human Melanoma Cells, Jharna Miya

Theses

RNA-sequencing refers to the use of high throughput sequencing technologies that are used to sequence cDNA in order to get the complete information of a sample’s RNA content. The objective of this study is to analyze this data in different aspects and to characterize gene expression. Besides this characterization, the data was also used to investigate the effect of sequencing depth on gene expression measurements.

This research focuses on quantitative measurement of expression levels of genes and their transcripts. In this study, complementary DNA fragments of cultured human melanoma cells are sequenced and a total of 139,501,106 million 200-bp reads …

Performance Comparison Of Five Rna-Seq Alignment Tools, Yuanpeng Lu

Theses

Aligning millions of short reads to a reference genome is a critical task in high throughput sequencing. In recent years, a large number of mapping algorithms have been developed, all of which have in common that they align a vast number of reads to genomic or transcriptomic sequences. RNA-Seq data is discrete in nature, therefore with reasonable gene models and comparative metrics RNA-Seq data can be simulated to sufficient accuracy to enable meaningful benchmarking of alignment algorithms. To provide guidance in the choice of alignment algorithms, five different alignment tools for RNA-Seq data are evaluated. In order to compare the …

Polyaseeker: A Computational Framework For Identifying Polyadenylation Cleavage Site From Rna-Seq, Xiao Ling

Theses

Alternative polyadenylation (APA) of mRNA plays a crucial role for post-transcriptional gene regulation. Recently, advances in next generation sequencing technology have made it possible to efficiently characterize the transcriptome and identify the 3’end of polyadenylated RNAs. However, no comprehensive bioi nformatic pipelines have fulfilled this goal. The PolyASeeker, a computational framework for identifying polyadenylation cleavage sites from RNA-Seq data is proposed in this thesis. By using the simulated RNA-seq dataset, a novel method is developed to evaluate the performance of the proposed framework versus the traditional A-stretch approach, and compute accurate Precisions and Recalls that previous estimation could not get. …

A Semantic Situation Awareness Framework For Indoor Cyber-Physical Systems, Pratikkumar Desai

Kno.e.sis Publications

Recently, the domain of cyber-physical systems (CPSs) has emerged as a successor to the traditional embedded systems and the wireless sensor networks. The relatively new cyber-physical domain offers tight integration of control, communication and computation components to develop advanced web based application in various heterogeneous domains such as health care, disaster management, automation and environment monitoring. The applications of indoor CPSs include remote patient monitoring, smart home, etc. with focus on situation awareness via event identification from context information. The principal challenges associated with the development of situation awareness applications include uncertainty in contextual data, incomplete domain knowledge, interoperability between …

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

Computer Science: Faculty Publications and Other Works

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …

Beta Atomic Contacts: Identifying Critical Specific Contacts In Protein Binding Interfaces, Qian Lu, Chee Keong Kwoh, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the …

Predicting Parkinson's Disease Progression With Smartphone Data, Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit P. Sheth

Kno.e.sis Publications

Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group.

What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt

Kno.e.sis Publications

The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators associated with conversation analysis in social science, we model the presence of conversation in the communication landscape of Twitter in a large corpus of 1.5M tweets for various disaster and non-disaster events spanning different periods, lengths of time and varied social significance. Within Replies, Retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic …

Towards Personalized Medicine Using Systems Biology And Machine Learning, Calin Voichita

Wayne State University Dissertations

The rate of acquiring biological data has greatly surpassed our ability to interpret it. At the same time, we have started to understand that evolution of many diseases such as cancer, are the results of the interplay between the disease itself and the immune system of the host. It is now well accepted that cancer is not a single disease, but a “complex collection of distinct genetic diseases united by common hallmarks”. Understanding the differences between such disease subtypes is key not only in providing adequate treatments for known subtypes but also identifying new ones. These unforeseen disease subtypes are …

A Hybrid Approach To Finding Relevant Social Media Content For Complex Domain Specific Information Needs, Delroy H. Cameron, Amit P. Sheth, Nishita Jaykumar, Gaurish Anand, Krishnaprasad Thirunarayan, Gary Alan Smith

Kno.e.sis Publications

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex, domain specific information needs. Some complex search situations require knowledge of both ontological concepts as well as 'intelligible constructs' not typically modeled in ontologies. Intelligible constructs convey essential information, which may be important to the holistic information needs of information seekers. Such constructs may include notions of intensity, frequency, interval, dosage, emotion, sentiment, equivalence, synonymy, negation, parts-of-speech, etc. However, few search systems utilize both structured background knowledge (ontologies) and the aforementioned knowledge for query interpretation in domain specific searches. Instead, there is …

Traffic Analytics Using Probabilistic Graphical Models Enhanced With Knowledge Bases, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Graphical models have been successfully used to deal with uncertainty, incompleteness, and dynamism within many domains. These models built from data often ignore preexisting declarative knowledge about the domain in the form of ontologies and Linked Open Data (LOD) that is increasingly available on the web. In this paper, we present an approach to leverage such 'top-down' domain knowledge to enhance 'bottom-up' building of graphical models. Specifically, we propose three operations on the graphical model structure to enrich it with nodes, edges, and edge directions. We illustrate the enrichment process using traffic data from 511.org and declarative knowledge from ConceptNet. …

Advancing Data Reuse In Phyloinformatics Using An Ontology-Driven Semantic Web Approach, Maryam Panahiazar, Amit P. Sheth, Ajith Harshana Ranabahu, Rutger Vos, Jim Leebens-Mack

Kno.e.sis Publications

Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web …

Twitris: Socially Influenced Browsing, Ashutosh Sopan Jadhav, Wenbo Wang, Raghava Mutharaju, Pramod Anantharam, Vinh Nguyen, Amit P. Sheth, Karthik Gomadam, Meenakshi Nagarajan, Ajith Harshana Ranabahu

Kno.e.sis Publications

In this paper, we present Twitris, a semantic Web application that facilitates browsing for news and information, using social perceptions as the fulcrum. In doing so we address challenges in large scale crawling, processing of real time information, and preserving spatio-temporal-thematic properties central to observations pertaining to real time events. We extract metadata about events from Twitter and bring related news and Wikipedia articles to the user. In developing Twitris, we have used the DBPedia ontology.

Adaptive Semantic Annotation Of Entity And Concept Mentions In Text, Pablo N. Mendes

Kno.e.sis Publications

The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.
These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a …