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  • Fatemeh Vafaee
Fatemeh Vafaee

Fatemeh Vafaee
UNSW Sydney | UNSW · School of Biotechnology and Biomolecular Sciences (BABS)

PhD

About

70
Publications
5,835
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707
Citations

Publications

Publications (70)
Article
Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen often adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expres...
Article
Liquid biopsy has shown promise for cancer diagnosis due to its minimally invasive nature and the potential for novel biomarker discovery. However, the low concentration of relevant blood-based biosources and the heterogeneity of samples (i.e. the variability of relative abundance of molecules identified), pose major challenges to biomarker discove...
Preprint
Different omics profiles, depending on the underlying technology, encompass measurements of several hundred to several thousands of molecules in a biological sample or a cell. This study develops upon the concept of "omics imagification" as a process of transforming a vector representing these numerical measurements into an image with a one-to-one...
Preprint
Different omics profiles, depending on the underlying technology, encompass measurements of several hundred to several thousands of molecules in a biological sample or a cell. This study develops upon the concept of "omics imagification" as a process of transforming a vector representing these numerical measurements into an image with a one-to-one...
Article
Full-text available
Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subt...
Article
Full-text available
Immunotherapy (IO), involving the use of immune checkpoint inhibition, achieves improved response-rates and significant disease-free survival for some cancer patients. Despite these beneficial effects, there is poor predictability of response and substantial rates of innate or acquired resistance, resulting in heterogeneous responses among patients...
Preprint
Long non-coding RNAs (lncRNAs) are emerging as key regulators in many biological processes. The dysregulation of lncRNA expression has been associated with many diseases, including cancer. Mounting evidence suggests that lncRNAs are involved in cancer initiation, progression, and metastasis. Thus, understanding the functional implications of lncRNA...
Preprint
Liquid biopsy has shown promise for cancer diagnosis due to its minimally invasive nature and the potential for novel biomarker discovery. However, the low concentration of relevant blood-based biosources and the heterogeneity of samples (i.e. the variability of relative abundance of molecules identified), pose major challenges to biomarker discove...
Article
Full-text available
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health and economic crisis worldwide which united global efforts to develop rapid, precise, and cost-efficient diagnostics, vaccines, and therapeutics. Numerous multi-disciplinary studies and techniques have been designed to investigate and develop various approac...
Article
Full-text available
Phospholipase A2 (PLA2) enzymes were first recognized as an enzyme activity class in 1961. The secreted (sPLA2) enzymes were the first of the five major classes of human PLA2s to be identified and now number nine catalytically-active structurally homologous proteins. The best-studied of these, group IIA sPLA2, has a clear role in the physiological...
Article
A typical single-cell RNA sequencing (scRNA-seq) experiment will measure on the order of 20 000 transcripts and thousands, if not millions, of cells. The high dimensionality of such data presents serious complications for traditional data analysis methods and, as such, methods to reduce dimensionality play an integral role in many analysis pipeline...
Preprint
Full-text available
An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http://vafaeelab.com/COVID19repositioning.html), that enables a visual an...
Preprint
An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http://vafaeelab.com/COVID19repositioning.html), that enables a visual an...
Article
Full-text available
An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http://vafaeelab.com/COVID19repositioning.html), that enables a visual an...
Preprint
Full-text available
A typical single-cell RNA sequencing (scRNA-seq) experiment will measure on the order of 20,000 transcripts and thousands, if not millions, of cells. The high dimensionality of such data presents serious complications for traditional data analysis methods and, as such, methods to reduce dimensionality play an integral role in many analysis pipeline...
Article
Full-text available
Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor microenvironment and are responsible for producing the desmoplastic reaction that is a poor prognostic factor in ovarian cancer. Long non-coding RNAs (lncRNAs) have been shown to play important roles in cancer. However, very little is known about the role of lncRNAs i...
Article
Full-text available
We and others have previously demonstrated the potential for circulating exosome microRNAs to aid in disease diagnosis. In this study, we sought the possible utility of serum exosome microRNAs as biomarkers for disease activity in multiple sclerosis patients in response to fingolimod therapy. We studied patients with relapsing-remitting multiple sc...
Article
Full-text available
Analysis of cancer mutational signatures have been instrumental in identification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly interface for...
Article
Full-text available
Protein oxidation sits at the intersection of multiple signalling pathways, yet the magnitude and extent of crosstalk between oxidation and other post-translational modifications remains unclear. Here, we delineate global changes in adipocyte signalling networks following acute oxidative stress and reveal considerable crosstalk between cysteine oxi...
Conference Paper
BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy in women, with high-grade serous ovarian cancer (HGSOC) the most common and aggressive subtype. The tumor microenvironment is acknowledged to play a vital role in the growth and metastasis of many solid tumors, including ovarian cancer, and as such represents an attractive new t...
Article
Full-text available
Bayesian networks (BNs) constitute a powerful framework for probabilistic reasoning and have been extensively used in different research domains. This paper presents an improved hybrid learning strategy that features parameterized genetic algorithms (GAs) to learn the structure of BNs underlying a set of data samples. The performance of GAs is infl...
Article
Full-text available
Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic ap...
Preprint
Full-text available
Analyses of large somatic mutation datasets, using advanced computational algorithms, have revealed at least 30 independent mutational signatures in tumor samples. These studies have been instrumental in identification and quantification of responsible endogenous and exogenous molecular processes against cancer. The quantitative approach used to de...
Article
Full-text available
Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to...
Article
Full-text available
Cancer-associated fibroblasts (CAFs) contribute to the poor prognosis of ovarian cancer. Unlike in tumour cells, DNA mutations are rare in CAFs, raising the likelihood of other mechanisms that regulate gene expression such as long non-coding RNAs (lncRNAs). We aimed to identify lncRNAs that contribute to the tumour-promoting phenotype of CAFs. RNA...
Conference Paper
Bayesian Network (BN) structure learning is a complex search problem, generally characterized by multimodality and epistasis. Genetic Algorithms (GAs) have been extensively used to pursue the BN structure learning task. This paper presents a new approach which incorporates the structural properties of the problem into GA mechanisms. The proposed ap...
Article
Full-text available
Transcription factors (TFs) play a fundamental role in coordinating biological processes in response to stimuli. Consequently, we often seek to determine the key TFs and their regulated target genes (TGs) amidst gene expression data. This requires a knowledge-base of TF-TG interactions, which would enable us to determine the topology of the transcr...
Data
Rankings of the biochemistry techniques used to detect TF-TG interactions included in ORTI. (PDF)
Data
Performance of ORTI as compared to other TF-TG interaction databases in identifying modulated TFs when just the Rank 1 data were considered (Table A); the parameters of Table 2 enrichment tests (Table B); functional terms enriched by TGs included in kernel sets of AR (Table C) and SREBF1 (Table D) using MSigDB; details of preprocessing and differen...
Data
List of kernel set TGs and DE genes with KSC p-value < 0.05 (i.e., potential novel TGs) in AR and SREBF1 case studies. (XLSX)
Article
In response to stimuli, biological processes are tightly controlled by dynamic cellular signaling mechanisms. Reversible protein phosphorylation occurs on rapid time-scales (milliseconds to seconds), making it an ideal carrier of these signals. Advances in mass spectrometry-based proteomics have led to the identification of many tens of thousands o...
Data
Comparison of automatic training set curated by KSR-LIVE and manually curated training set. A) Overlap of Akt (left) and mTOR (right) training sets. B) Scatter plot of prediction scores using the KSR-LIVE training set (y-axis) and the manually curated training set (x-axis). KSR-LIVE training set is shown in blue, the manually curated training set i...
Data
Identified kinase substrate relationships. This table lists all substrates that make up the characteristic temporal response of a kinase. (XLSX)
Data
Prediction score for Akt and Rps6kb1. Table of all sites and the kinase prediction score for Akt and Rps6kb1 as well as the sites used as training sets. (XLSX)
Article
Full-text available
Heterogeneity is a hallmark of glioblastoma with intratumoral heterogeneity contributing to variability in responses and resistance to standard treatments. Promoter methylation status of the DNA repair enzyme O6-methylguanine DNA methyltransferase (MGMT) is the most important clinical biomarker in glioblastoma, predicting for therapeutic response....
Conference Paper
Full-text available
Table of contents A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laene...
Article
Full-text available
Biomarkers have gained immense scientific interest and clinical value in the practice of medicine. With unprecedented advances in high-throughput technologies, research interest in identifying novel and customized disease biomarkers for early detection, diagnosis, or drug responses is rapidly growing. Biomarkers can be identified in different level...
Article
Full-text available
Alzheimer's disease (AD) is a complex, multifactorial disease that has reached global epidemic proportions. The challenge remains to fully identify its underlying molecular mechanisms that will enable development of accurate diagnostic tools and therapeutics. Conventional experimental approaches that target individual or small sets of genes or prot...
Article
Heterogeneity is a hallmark of glioblastoma with intratumoral heterogeneity contributing to variability in responses and resistance to standard treatments. DNA repair mechanisms are key elements involved in the response to temozolomide with epigenetic silencing of the O⁶-methylguanine methyltransferase (MGMT) promoter being a predictive biomarker f...
Article
Protein-protein interactions (PPIs) are useful for understanding signaling cascades, predicting protein function, associating proteins with disease and fathoming drug mechanism of action. Currently, only ∼10% of human PPIs may be known, and about one-third of human proteins have no known interactions. We introduce FpClass, a data mining-based metho...
Article
This paper is concerned with proposing an elitist genetic algorithm which makes use of a new mutation scheme aimed to tackle both explorative and exploitative responsibilities of genetic operators. The proposed mutation scheme follows an approach similar to motif representation in biology, to derive the underlying pattern of highly-fit solutions di...
Article
Bayesian networks are probabilistic graphical models representing conditional dependencies among a set of random variables. Due to their concise representation of the joint probability distribution, Bayesian Networks are becoming incrementally popular models for knowledge representation and reasoning in various problem domains. However, learning th...
Conference Paper
Exploration and exploitation are the two cornerstones which characterize Evolutionary Algorithms (EAs) capabilities. Maintaining the reciprocal balance of the explorative and exploitative power is the key to the success of EA applications. Accordingly, this work is concerned with proposing a diversity-guided genetic algorithm with a new mutation sc...
Article
Full-text available
Background Elucidation of the direct/indirect protein interactions and gene associations is required to fully understand the workings of the cell. This can be achieved through the use of both low- and high-throughput biological experiments and in silico methods. We present GAP (Gene functional Association Predictor), an integrative method for predi...
Conference Paper
Exploration and exploitation are the two cornerstones which characterize Evolutionary Algorithms (EAs) capabilities. Maintaining the reciprocal balance of the explorative and exploitative power is the key to the success of EA applications. Accordingly, in this work the canonical Genetic Algorithm is augmented by a new mutation scheme that is capabl...
Conference Paper
This work is concerned with proposing a robust framework for optimizing operator rates of simple Genetic Algorithms (GAs) during a GA run. The suggested framework is built upon a formerly proposed GA Markov chain model to estimate the optimal values of the operator rates based on the time and the current state of the evolution. Though the proposed...
Conference Paper
Dealing with many free parameters and finding an appropriate set of parameter values for an evolutionary algorithm (EA) has been a longstanding major challenge of the evolutionary computation community. Such difficulty has directed researchers' attention towards devising an automated ways of controlling EA parameters. This work is concerned with pr...
Conference Paper
In this work a novel approach is proposed to adaptively adjust genetic operator probabilities through the adoption of a robust, real-valued optimization algorithm known as Differential Evolution (DE). We set up a series of experiments on a wide array of symbolic regression problems. The experimental results demonstrate the supremacy of our proposed...
Conference Paper
Full-text available
The in-network query processing paradigm in sensor networks postulates that a query is routed among sensors and collects the answers from the sensors on its trajectory. It works for static and connected sensor networks. However, when the network consists of mobile sensors and is sparse, a different approach is necessary. In this paper we propose a...
Chapter
Full-text available
We propose a new method of dynamically adapting the probabilities of genetic operators based on the global behavior of the population for each generation. The proposed method consists of two main components which are assigning credits to operators according to the fitness improvements of the individuals, and updating the operators’ probabilities at...
Conference Paper
This work is concerned with proposing an adaptive method to dynamically adjust genetic operator probabilities throughout the evolutionary process. The proposed method relies on the individual preferences of each chromosome, rather than the global behavior of the whole population. Hence, each individual carries its own set of parameters, including t...

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