
Wikum DinalankaraUniversity of Maryland, College Park | UMD, UMCP, University of Maryland College Park · Center for Bioinformatics and Computational Biology
Wikum Dinalankara
PhD (Expected May 2015)
About
42
Publications
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Introduction
Additional affiliations
August 2009 - May 2015
Publications
Publications (42)
Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis practice. This is a demanding and costly process, and recent research has demonstrated that it is possible to utilize artificial intelligence (AI) algorithms to assist in the interpretive process. Here we report our examinatio...
In the complex tumor microenvironment (TME), mesenchymal cells are key players, yet their specific roles in prostate cancer (PCa) progression remain to be fully deciphered. This study employs single-cell RNA sequencing to delineate molecular changes in tumor stroma that influence PCa progression and metastasis. Analyzing mesenchymal cells from four...
Many gene signatures have been developed by applying machine learning (ML) on omics profiles, however, their clinical utility is often hindered by limited interpretability and unstable performance. Here, we show the importance of embedding prior biological knowledge in the decision rules yielded by ML approaches to build robust classifiers. We test...
Background
PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa.
Methods...
p>In this work we develop a framework which allows for a systematic analysis of joint DNA and putative downstream RNA effects in cancer data cohorts. Using the Reactome database, we extract gene pairs that are linked by known mechanistic connections. Such pairs, which we refer to as 9Source Target Pairs9 or STPs, consist of a source gene for which...
Cancer cells display massive dysregulation of key regulatory pathways due to now well-catalogued mutations and other DNA-related aberrations. Moreover, enormous heterogeneity has been commonly observed in the identity, frequency and location of these aberrations across individuals with the same cancer type or subtype, and this variation naturally p...
Machine learning (ML) algorithms are used to build predictive models or classifiers for specific disease outcomes using transcriptomic data. However, some of these models show deteriorating performance when tested on unseen data which undermines their clinical utility.
In this study, we show the importance of directly embedding prior biological kno...
Since the beginning of the coronavirus disease-2019 (COVID-19) pandemic in 2020, there has been a tremendous accumulation of data capturing different statistics including the number of tests, confirmed cases and deaths. This data wealth offers a great opportunity for researchers to model the effect of certain variables on COVID-19 morbidity and mor...
The COVID-19 mortality rate is higher in the elderly and in those with pre-existing chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infections; thus, an annual influenza vaccination is recommended for them. In this study, we explore a possible county-level association between influe...
Given the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from a given ba...
Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of...
Cancer cells are adept at reprogramming energy metabolism and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of...
PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. Here, we applied a meta-analysis approach, leveraging two large PCa cohorts with experimentally validated PTEN...
Phosphatase and tensin homologue (PTEN) is a tumor suppressor gene that is frequently inactivated by deletion in prostate cancer (PCa). Occurring in around 20% of primary PCa tumors, and up to 50% in castration resistant tumors, it is the most frequent genomic aberration in PCa. Loss of PTEN activates the phosphoinositide 3-kinase-RAC-alpha serine/...
Usually recognized as transcripts of length more than 200 bp and devoid of open reading frames, long non-coding RNAs (lncRNAs) span a vast range of the human genome. Once thought to be of relatively little biological importance, they have been shown to be involved in many biological processes and diseases, highlighting their important regulatory fu...
COVID-19 mortality rate is higher in the elderly and in those with preexisting chronic medical conditions. The elderly also suffer from increased morbidity and mortality from seasonal influenza infection, and thus annual influenza vaccination is recommended for them.
In this study, we explore a possible area-level association between influenza vacc...
Cancer cells display massive dysregulation of key regulatory pathways due to now well-catalogued mutations and other DNA-related aberrations. Moreover, enormous heterogeneity has been commonly observed in the identity, frequency, and location of these aberrations across individuals with the same cancer type or subtype, and this variation naturally...
In recent years, immunotherapy has become one of the most exciting and promising avenues to cancer treatment. Treatment with immune checkpoint inhibitors has managed to produce long-term remission of solid tumors in many patients. However, patients who respond well to such treatment are often a minority; this is particularly the case with some canc...
Long noncoding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes including human diseases. We present here FC-R2, a comprehensive expression atlas across a broadly defined human transcriptome, in...
A bstract
Given the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from...
The three-prime untranslated region (3'-UTR) of a mRNA influences its biological behavior, from stability, post-transcriptional control through miRNAs, and availability for translation. Alternative polyadenylation (APA) can modulate 3' end site selection, and approximately 50% of coding genes are subject to it. Global transcript shortening has been...
Long non-coding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes including disease. We present hereFC-R2, a comprehensive expression atlas across a broadly-defined human transcriptome, inclusive...
Androgen receptor (AR) transcriptional activity contributes to prostate cancer development and castration resistance. The growth and survival pathways driven by AR remain incompletely defined. Here, we found PDCD4 to be a new target of AR signaling and a potent regulator of prostate cancer cell growth, survival, and castration resistance. The 3′ un...
It remains unclear whether PAX6 acts as a crucial transcription factor for lung cancer stem cell (CSC) traits. We demonstrate that PAX6 acts as an oncogene responsible for induction of cancer stemness properties in lung adenocarcinoma (LUAD). Mechanistically, PAX6 promotes GLI transcription, resulting in SOX2 upregulation directly by the binding of...
In recent years, in depth exploration of genomes structure and function has revealed a central role for non-coding RNAs (ncRNAs) in orchestrating key biological and cellular processes through the fine tuning of gene expression regulation. Most importantly a role for ncRNAs has also started to emerge in human disease pathogenesis. This further speak...
Significance
Technological advances enable increasingly comprehensive profiling of the molecular landscapes of cells, and these data can inform the personalized treatment of complex diseases. Two major obstacles are the complexity of these data and the high degree of person-to-person heterogeneity. We develop a highly simplified, personalized data...
Overcoming acquired drug resistance remains a core challenge in the clinical management of human cancer, including in urothelial carcinoma of the bladder (UCB). Cancer stem-like cells (CSC) have been implicated in the emergence of drug resistance but mechanisms and intervention points are not completely understood. Here, we report that the proinfla...
Motivation: Complex cancer omics data can be difficult to interpret and analyze with standard statistical methods. We thereby propose an innovative data representation that drastically reduces complexity while improving usability and interpretability for complex cancer phenotype analysis.
Method: Despite recent advances in omics technologies, the r...
Renal cell carcinomas (RCCs) with Xp11 translocation (Xp11 RCC) constitute a distinctive molecular subtype characterized by chromosomal translocations involving the Xp11.2 locus, resulting in gene fusions between the TFE3 transcription factor with a second gene (usually ASPSCR1, PRCC, NONO, or SFPQ). RCCs with Xp11 translocations comprise up to 1–4...
Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly vari...
Supplementary Table 1. A summary of the gene expression microarray datasets used.
Supplementary Table 2. A summary of the DNA methylation datasets used.
Supplementary Figure 1. Anti-profiles applied to methyl ation data: (A) Distribution of anti-profile scores for adenoma and carcinoma for thyroid tumor samples from methylation data (AUC = 0.784, W...
Anomaly detection is a classical problem in Statistical Learning with wide-reaching applications in security, networks, genomics and others. In this work, we formulate the anomaly classification problem as an extension to the detection problem: how to distinguish between samples from multiple heterogenous classes that are anomalies relative to a we...
We introduce the anti-profile Support Vector Machine (apSVM) as a novel
algorithm to address the anomaly classification problem, an extension of
anomaly detection where the goal is to distinguish data samples from a number
of anomalous and heterogeneous classes based on their pattern of deviation from
a normal stable class. We show that under heter...
What commonsense knowledge do intelligent systems need, in order to recover from failures or deal with unexpected situations? It is impractical to represent predetermined solutions to deal with every unanticipated situation or provide predetermined fixes for all the different ways in which systems may fail. We contend that intelligent systems requi...
Contemporary machine intelligence is far from realizing prominent hallmarks of human understanding and consciousness. The primary shortcoming of current methods can be attributed to the difficulty or implausibility of foreseeing and pre-programming each and every piece of information or knowledge. Emergent intelligence methods based on principles o...