
Raghvendra Mall- Doctor of Philosophy
- Director at Technology Innovation Institute
Raghvendra Mall
- Doctor of Philosophy
- Director at Technology Innovation Institute
In hot pursuit of translational research
About
158
Publications
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Introduction
Life is all about learning and research. I am experienced machine learning researcher with expertise in Data Sciences, Systems Biology, Complex Networks, and Computational Immunology (>14 years post-MS) -- working on multi-omics driven biological insights to understand disease vagaries, identify therapeutic targets, and translate to clinical practice. I specialize in scientific team leadership and cross-cultural collaborations, with experience managing international research projects.
Current institution
Additional affiliations
Education
April 2012 - July 2015
Publications
Publications (158)
We propose a generic framework for gene regulatory network (GRN) inference approached as a feature selection problem. GRNs obtained using Machine Learning techniques are often dense, whereas real GRNs are rather sparse. We use a Tikonov regularization inspired optimal L-curve criterion that utilizes the edge weight distribution for a given target g...
Motivation
Protein solubility plays a vital role in pharmaceutical research and production yield. For a given protein, the extent of its solubility can represent the quality of its function, and is ultimately defined by its sequence. Thus, it is imperative to develop novel, highly accurate in silico sequence-based protein solubility predictors.
Me...
Resistance to programmed cell death (PCD) is a hallmark of cancer. While some PCD components are prognostic in cancer, the roles of many molecules can be masked by redundancies and crosstalks between PCD pathways, impeding the development of targeted therapeutics. Recent studies characterizing these redundancies have identified PANoptosis, a unique...
In tumor-bearing mice, cyclic fasting or fasting-mimicking diets (FMD) enhance the activity of antineoplastic treatments by modulating systemic metabolism and boosting antitumor immunity. Here we conducted a clinical trial to investigate the safety and biological effects of cyclic, five-day FMD in combination with standard antitumor therapies. In 1...
A cancer immune phenotype characterized by an active T-helper 1 (Th1)/cytotoxic response is associated with responsiveness to immunotherapy and favorable prognosis across different tumors. However, in some cancers, such an intratumoral immune activation does not confer protection from progression or relapse. Defining mechanisms associated with immu...
Drug toxicity and market withdrawals are two issues that often obstruct the lengthy and intricate drug discovery process. In order to enhance drug effectiveness and safety, this review examines withdrawn drugs and presents a novel paradigm for their redesign. In addition to addressing methodological issues with toxicity datasets, this study highlig...
The problem of protein structure determination is usually solved by X-ray crystallography. Several in silico deep learning methods have been developed to overcome the high attrition rate, cost of experiments and extensive trial-and-error settings, for predicting the crystallization propensities of proteins based on their sequences. In this work, we...
Human leukocyte antigen or HLA plays a crucial
role in the recognition of antigenic peptides as this binding is
responsible for subsequent immune response by eliciting T-cell
activation. Accurate prediction of peptide-HLA binding affinity is
imperative for facilitating vaccine development and immunother-
apies. Recent advancements in transformer-ba...
Background
While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials and case reports. These observations suggest that a molecular basis for effective immunity may exist within a subpopulation of HGSC. Herein, we developed an...
Background
Obesity stands as a formidable public health challenge, contributing to a spectrum of diseases, including cardiovascular disorders, and type 2 diabetes mellitus. Individuals with obesity classified as “metabolically healthy” have susceptibility to various diseases later in life. These diseases often linked to dysregulated metabolic pathw...
Objectives
Diabetes secondary to chronic pancreatitis (CP) presents clinical challenges due to insulin secretory defects and associated metabolic alterations. Owing to lack of molecular understanding, no pharmacotherapies to treat insulin secretory defects have been approved to date. We aimed to delineate the molecular mechanism of β-cell dysfuncti...
The problem of protein structure determination is usually solved by X-ray crystallography. Several in silico deep learning methods have been developed to overcome the high attrition rate, cost of experiments and extensive trial-and-error settings, for the predicting the crystallization propensities of proteins based on their sequences. In this work...
Peptide- and protein-based therapeutics are becoming a promising treatment regimen for myriad diseases. Toxicity of proteins is the primary hurdle for protein-based therapies. Thus, there is an urgent need for accurate in silico methods for determining toxic proteins to filter the pool of potential candidates. At the same time, it is imperative to...
NLRs constitute a large, highly conserved family of cytosolic pattern recognition receptors that are central to health and disease, making them key therapeutic targets. NLRC5 is an enigmatic NLR with mutations associated with inflammatory and infectious diseases, but little is known about its function as an innate immune sensor and cell death regul...
Background
The innate immune system serves as the first line of host defense. Transforming growth factor-β–activated kinase 1 (TAK1) is a key regulator of innate immunity, cell survival, and cellular homeostasis. Because of its importance in immunity, several pathogens have evolved to carry TAK1 inhibitors. In response, hosts have evolved to sense...
Technology-mediated group toxicity polarization is a major socio-technological issue of our time. For better large-scale monitoring of polarization among social media news content, we quantify the toxicity of news video comments using a Toxicity Polarization Score. For polarizing news videos, our premise is that the comments’ toxicity approximates...
Innate immunity provides the first line of defense through multiple mechanisms, including pyrogen production and cell death. While elevated body temperature during infection is beneficial to clear pathogens, heat stress (HS) can lead to inflammation and pathology. Links between pathogen exposure, HS, cytokine release, and inflammation have been obs...
Background
Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled cli...
An accurate binding affinity prediction between T-cell receptors and epitopes contributes decisively to develop successful immunotherapy strategies. Some state-of-the-art computational methods implement deep learning techniques by integrating evolutionary features to convert the amino acid residues of cell receptors and epitope sequences into numer...
The importance of inflammatory cell death, PANoptosis, in cancer is increasingly being recognized. PANoptosis can promote or inhibit tumorigenesis in context-dependent manners, and a computational approach leveraging transcriptomic profiling of genes involved in PANoptosis has shown that patients can be stratified into PANoptosis High and PANoptosi...
The COVID-19 pandemic, caused by the β-coronavirus (β-CoV) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to cause significant global morbidity and mortality. While vaccines have reduced the overall number of severe infections, there remains an incomplete understanding of viral entry and innate immune activation, which can...
Background
Tumor invasiveness reflects numerous biological changes, including tumorigenesis, progression, and metastasis. To decipher the role of transcriptional regulators (TR) involved in tumor invasiveness, we performed a systematic network-based pan-cancer assessment of master regulators of cancer invasiveness.
Materials and methods
We stratif...
Cytosolic innate immune sensors are critical for host defense and form complexes, such as inflammasomes and PANoptosomes, that induce inflammatory cell death. The sensor NLRP12 is associated with infectious and inflammatory diseases, but its activating triggers and roles in cell death and inflammation remain unclear. Here, we discovered that NLRP12...
The lack of multi-omics cancer datasets with extensive follow-up information hinders the identification of accurate biomarkers of clinical outcome. In this cohort study, we performed comprehensive genomic analyses on fresh-frozen samples from 348 patients affected by primary colon cancer, encompassing RNA, whole-exome, deep T cell receptor and 16S...
Transforming growth factor-β-activated kinase 1 (TAK1) is a central regulator of innate immunity, cell death, inflammation, and cellular homeostasis. Therefore, many pathogens carry TAK1 inhibitors (TAK1i). As a host strategy to counteract this, inhibition or deletion of TAK1 induces spontaneous inflammatory cell death, PANoptosis, through the RIPK...
Objectives
To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways.
Methods
We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured i...
Monkeypox virus (MPXV) was confirmed in May 2022 and designated a global health emergency by WHO in July 2022. MPX virions are big, enclosed, brick-shaped, and contain a linear, double-stranded DNA genome as well as enzymes. MPXV particles bind to the host cell membrane via a variety of viral-host protein interactions. As a result, the wrapped stru...
Motivation
To examine the hypothesis that obesity with metabolic syndrome, compared to simple obesity, has distinct molecular signatures and metabolic pathways.
Methods
We analyzed a cohort of 39 patients with obesity that includes 21 subjects with metabolic syndrome, age-matched to 21 subjects with simple obesity. We measured in whole blood sampl...
Purpose: Predictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled cli...
Non-alcoholic fatty liver disease (NAFLD) is a common liver lesion that is untreatable with medications. Glucagon-like peptide-1 receptor (GLP-1R) agonists have recently emerged as a potential NAFLD pharmacotherapy. However, the molecular mechanisms underlying these drugs’ beneficial effects are not fully understood. Using Fourier transform infrare...
Type I interferons (IFNs) are essential innate immune proteins that maintain tissue homeostasis through tonic expression and can be upregulated to drive antiviral resistance and inflammation upon stimulation. However, the mechanisms that inhibit aberrant IFN upregulation in homeostasis and the impacts of tonic IFN production on health and disease r...
Background
Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognosti...
Background: Obesity coexists with variable features of metabolic syndrome, which is associated with dysregulated metabolic pathways. We assessed potential associations between serum metabolites and features of metabolic syndrome in Arabic subjects with obesity. Methods: We analyzed a dataset of 39 subjects with obesity only (OBO, n = 18) age-matche...
Background
Obesity-associated dysglycemia is associated with metabolic disorders. MicroRNAs (miRNAs) are known regulators of metabolic homeostasis. We aimed to assess the relationship of circulating miRNAs with clinical features in obese Qatari individuals.
Methods
We analyzed a dataset of 39 age-matched patients that includes 18 subjects with obe...
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), continues to cause significant morbidity and mortality in the ongoing global pandemic. Understanding the fundamental mechanisms that govern innate immune and inflammatory responses during SARS-CoV-2 infection is critical for...
Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of E...
We recently found by single-cell mass cytometry that ex vivo human B cells internalize graphene oxide (GO). The functional impact of such uptake on B cells remains unexplored. Here, we disclosed the effects of GO and amino-functionalized GO (GONH2) interacting with human B cells in vitro and ex vivo at the protein and gene expression levels. Moreov...
Traumatic brain injury (TBI) can be defined as a disorder in the function of the brain after a bump, blow, or jolt to the head, or penetrating head injury. Mild traumatic brain injury (mTBI) can cause devastating effects, such as the initiation of long-term neurodegeneration in brain tissue. In the current study, the effects of mTBI were investigat...
Poor sleep quality has been linked to several chronic, psychiatric, and neurological conditions that can burden the public health system. This paper aims to develop methods to assess sleep quality from physical activity data collected from wearable devices. Our methods can be deployed on a large scale and used by recommender systems to guide the pu...
Mixing cations has been a successful strategy in perovskite synthesis by solution-processing, delivering improvements in the thermodynamic stability as well as in the lattice parameter control. Unfortunately, the relation between a given cation mixture and the associated structural deformation is not well-established, a fact that hinders an adequat...
We introduce Permutation and Structured Perturbation Inference (PSPI), a new problem formulation that abstracts many graph matching tasks that arise in systems biology. PSPI can be viewed as a robust formulation of the permutation inference or graph matching, where the objective is to find a permutation between two graphs under the assumption that...
Motivation:
A global effort is underway to identify compounds for the treatment of COVID-19. Since de novo compound design is an extremely long, time-consuming, and expensive process, efforts are underway to discover existing compounds that can be repurposed for COVID-19 and new viral diseases.
Model:
We propose a machine learning representation...
Motivation: A global effort is underway to identify drugs for the treatment of COVID-19. Since de novo drug design is an extremely long, time-consuming, and expensive process, efforts are underway to discover existing drugs that can be repurposed for COVID-19.
Model: We propose a machine learning representation framework that uses deep learning-i...
In recent years, there has been a significant expansion in the development and use of multi-modal sensors and technologies to monitor physical activity, sleep and circadian rhythms. These developments make accurate sleep monitoring at scale a possibility for the first time. Vast amounts of multi-sensor data are being generated with potential applic...
Aims
The progression from prediabetes to type 2 diabetes is preventable by lifestyle intervention and/or pharmacotherapy in a large fraction of individuals with prediabetes. Our objective was to develop a risk score to screen for prediabetes in Middle East, where diabetes prevalence is one of the highest in the world.
Materials and methods
In this...
Given the surging growth of artificial-intelligence-inspired computational methods in materials science, experimental laboratories around the globe have become open to adopting data-driven approaches for materials discovery. The field witnesses emerging machine-learning models trained over databases, of which data are collected from high-throughput...
Objective
To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.
Patients and Methods
Thirteen patients (10 males and three females) with...
div>Motivation: A global effort is underway to identify drugs for the treatment of COVID-19. Since de novo drug design is an extremely long, time-consuming, and expensive process, efforts are underway to discover existing drugs that can be
repurposed for COVID-19.
Model: We propose a machine learning representation framework that uses deep learni...
About the Cover: Guided by machine learning predictors and with minimal laboratory synthesis trial-and-error, mixed cation compositions of lead halide perovskites that recover the cubic structure at room temperature are revealed.
http://dx.doi.org/10.1021/acs.chemmater.9b05342
Background
An immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown.
Methods
To explore the contextual prognostic value of cance...
Data-driven approaches for materials design and selection have accelerated materials discovery along with the upsurge of machine learning applications. We report here a prediction-to-lab-scale synthesis of cubic phase triple-cation lead halide perovskites guided by a machine-learning perovskite stability predictor. The starting double-cation perovs...
Amyloid fibrillation is the root cause of several neuro as well as non-neurological disorders. Understanding the molecular basis of amyloid aggregate formation is crucial for deciphering various neurodegenerative diseases. In our study, we have examined the lysozyme fibrillation process using nano-infrared spectroscopy (nanoIR). NanoIR enabled us t...
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to specific bNAbs. Currently, resistant...
Motivation:
X-ray crystallography has facilitated the majority of protein structures determined to date. Sequence-based predictors that can accurately estimate protein crystallization propensities would be highly beneficial to overcome the high expenditure, large attrition rate, and to reduce the trial-and-error settings required for crystallizati...
Interactions between programmed death-1 (PD-1) with its ligand PD-L1 on tumor cells can antagonize T cell responses. Inhibiting these interactions using immune checkpoint inhibitors has shown promise in cancer immunotherapy. MDA-MB-231 is a triple negative breast cancer cell line that expresses PD-L1. In this study, we investigated the biochemical...
https://pubs.acs.org/toc/jpcafh/123/33
Forecasting the structural stability of hybrid organic/inorganic compounds, where polyatomic molecules replace atoms, is a challenging task; the composition space is vast and the reference structure for the organic molecules is ambiguously defined. In this work we use a range of machine-learning algorithms, constructed from state-of-the-art density...
Accurately measuring sleep and its quality with polysomnography (PSG) is an expensive task. Actigraphy, an alternative, has been proven cheap and relatively accurate. However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atheros...
Motivation: Protein solubility is a property associated with protein expression and is a critical determinant of the manufacturability of therapeutic proteins. It is thus imperative to design accurate in-silico sequence-based solubility predictors.
Methods: In this study, we propose SolXplain, an extreme gradient boosting machine based protein solu...
Background
It is becoming clear that tumor immune T cell infiltration and its functional orientation have substantial effect on cancer progression, influencing both response to therapy and prognosis. In this pan-cancer study, the previously described Immunologic Constant of Rejection (ICR) signature is used to define opposing immune phenotypes (i.e...
Correction for ‘Exploring new approaches towards the formability of mixed-ion perovskites by DFT and machine learning’ by Heesoo Park et al. , Phys. Chem. Chem. Phys. , 2019, DOI: 10.1039/c8cp06528d.
Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competiti...
Recent years have witnessed a growing effort in engineering and tuning the properties of hybrid halide perovskites as light absorbers. These have led to the successful enhancement of their stability, a feature that is often counterbalanced by a reduction of their power-conversion efficiency. In order to provide a systematic analysis of the structur...
Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appropriate analysis tools. The performance of population-based (subjects are unrel...
Fourier Transform Infrared Spectroscopy (FTIR) is a non-destructive analytical technique that has been employed in this research to characterize the biochemical make-up of various rat brain regions. The sensorimotor cortex, caudate putamen, thalamus, and the hippocampus were found to have higher olefinic content—an indicator of a higher degree of u...
Motivation: Protein structure determination has primarily been performed using X-ray crystallography. To overcome the expensive cost, high attrition rate and series of trial-and-error settings, many in-silico methods have been developed to predict crystallization propensities of proteins based on their sequences. However, the majority of these meth...
Following publication of the original article [1], the authors reported that one of the authors’ names was processed incorrectly. In this Correction the incorrect and correct author name are shown. The original publication of this article has been corrected.
Objective: Stroke is the main cause of adult disability in the world, leaving more than half of the patients dependent on daily assistance. Understanding the post-stroke biochemical and molecular changes are critical for patient survival and stroke management. The aim of this work was to investigate the photo-thrombotic ischemic stroke in male rats...
The representative FTIR spectrum of white matter (WM) in a native control rat brain in the spectral range of 4000–700 cm-1 and mechanical properties of the native and lesioned brain sections. Representative FTIR spectra of WM in the native control rat brain from region 4000–700 cm-1.
Fourier transform Infrared (FTIR) spectral bands and their corresponding bio-chemical assignment.
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection with several undergoing clinical trials. Due to high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to particular bNAbs. Resistant strains are commonly ident...
This file describes the steps used in RGBM Framework for reverse-engineering GRN and using FGSEA along with differential expression of targets to identify the key master regulators. We then visualize the activity of the master regulators in the case vs the controls.
Background: Human tissues are invaluable resources for researchers worldwide. Biobanks are repositories of such human tissues and can have a strategic importance for genetic research, clinical care, and future discoveries and treatments. One of the aims of Qatar Biobank is to improve the understanding and treatment of common diseases afflicting Qat...
The goal of this paper is to develop a novel statistical frame-
work for inferring dependence between distributions of variables in omics data. We propose the concept of building a dependence network using a copula-based kernel dependency measures to reconstruct the underlying association network between the distributions. ISaaC is utilized for rev...
Disease processes are usually driven by several genes interacting in molecular modules or pathways leading to the disease. The identification of such modules in gene or protein networks is the core of computational methods in biomedical research. With this pretext, the Disease Module Identification (DMI) DREAM Challenge was initiated as an effort t...
Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competiti...