Ahmed Abdeen HamedSano Centre of Computational Medicine · Clinical Data Science
Ahmed Abdeen Hamed
Ph.D. Computer Science
Text Mining -- Drug Repurposing -- Combination Therapy -- Knowlege Graph
About
41
Publications
26,684
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
205
Citations
Citations since 2017
Introduction
Bridging the gap between the current state and our actual understanding of human diseases using means of algorithms and computational models.
Additional affiliations
July 2019 - present
Position
- Professor (Assistant)
Description
- * Developing a new Data Science concentration at Norwich University * Teaching Data Science, Data Analytics, Network Science * Research interested: Social Media and literature mining. Fact-checking. Misinformation.
August 2018 - present
December 2016 - May 2018
Education
August 2009 - May 2014
Field of study
- Computer Science, Data Mining, Artificial Intelligent, Machine Learning
Publications
Publications (41)
The importance of searching BioMedical literature for drug interaction and side-effects is apparent. Current digital libraries (e.g., PubMed) suffer infrequent tagging and metadata annotation updates. Such limitations cause absence of linking literature to new scientific evidence. This demonstrates a great deal of challenges that stand in the way o...
Background:
Driven by the desperate time and the dire need racing to discover an antiviral drug to save our fellow humans, we explored the landscape of the SARS-CoV-2 Biomedical publications to satisfy the following objectives.
Objective:
(1) identify off-label drugs that may bring benefit for the COVID-19 pandemic, (2) present a ranking algorit...
The spread of the Coronavirus pandemic has been accompanied by an infodemic. The false in-formation that is embedded in the infodemic affects people’s ability to have access to safety in-formation and follow proper procedures to mitigate the risks. This research aims to target the falsehood part of the infodemic, which prominently proliferates in n...
Though several vaccines are available, there is no guarantee that everyone will choose to be vaccinated. Also, with the virus constantly mutating and the world having to deal with both the Delta and Omicron variants, there is no clear evidence yet on how the available vaccines, in their current state, would prevent the spread. A need for comprehens...
This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the f...
This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the f...
Background:
With the Coronavirus becoming a new reality of our world, global efforts continue to seek answers to many questions regarding the spread, variants, vaccinations, and medications. Particularly, with the emergence of several strains (e.g., Delta, Omicron), vaccines will need further development to offer complete protection against the ne...
Biomedical scientists often search databases of therapeutic molecules to answer a set of molecule-related questions. When it comes to drugs, finding the most specific target is a crucial biological criterion. Whether the target is a gene, protein, and cell line, target specificity is what makes a therapeutic molecule significant. In this chapter, w...
The title of the manuscript presents the urgent topic of drug repurposing in the context of COVID-19. Clearly, research in this area is much needed, and the esteemed authors have put it well: “no time to lose.” The manuscript, however, suffers from some significant and obvious issues that can be summarized as follows
UNSTRUCTURED
This is a peer review submitted for MS#19583
Background:
Driven by the desperate time and the dire need racing to discover an antiviral drug to save our fellow humans, we explored the landscape of the SARS-CoV-2 Biomedical publications to satisfy the following objectives.
Objective:
(1) identify off-label drugs that may bring benefit for the COVID-19 pandemic, (2) present a ranking algorit...
BACKGROUND
Driven by the desperate time and the dire need racing to discover an antiviral drug to save our fellow humans, we explored the landscape of the SARS-CoV-2 Biomedical publications to satisfy the following objectives.
OBJECTIVE
(1) identify off-label drugs that may bring benefit for the COVID-19 pandemic, (2) present a ranking algorithm c...
Biomedical scientists often search databases of therapeutic molecules to answer a set of drug-related queries. In this paper, we present a novel network algorithm called MolecRank that is specialized in searching and ranking molecules using a biomedical literature. Starting with a disease-related set of publications (e.g., depression), a feature ex...
Biomedical scientists often search databases of therapeutic molecules to answer a set of drug-related queries. In this paper, we present a novel network algorithm called MolecRank that is specialized in searching and ranking molecules using a biomedical literature. Starting with a disease-related set of publications (e.g., depression), a feature ex...
Finding safe, non-toxic, and specific molecules to address a given research question is the dream of every Merck scientist. We propose a foresight mechanism that compiles various evidence from literature, clinical trials, and real-world data that can accelerate and focus this search process. By analyzing these resources together computationally we...
We present a work-in-progress novel algorithm called MolecRank that ranks molecules based on their mention in PubMed literature. We extract biological features (gene, chemical compound) from the abstracts, then we transform the features into a Linked Data format. The data is then ingested into a triple store to enable end users to perform semantic...
This paper presents a novel social network ranking algorithm
called CrRank, designed specifically for social media. The algorithm
computes the user ranks by analyzing the content they contribute in terms
of words and hashtags. The main intuition is based on the user subscriptions
to the various topics of a given dataset. Such subscription is me...
The Coupled impacts of climate and land use change across a river–lake continuum: insights from an integrated assessment model of Lake Champlain's Missisquoi Basin, 2000–2040 supplementary data article
Global climate change (GCC) is projected to bring higher-intensity precipitation and higher-variability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Incre...
Human induced climate change is one of this century's greatest unbalancing forces that affect our planet. Capturing the public awareness of climate change on Twitter has proven to be significant. We demonstrated in our previous research that public awareness is prominently expressed in the form of hashtags that uses more than one bigram (i.e., a cl...
In continuation of the ongoing efforts to understanding the climate change impact on Lake Champlain basin, we present the current status: Our previous efforts have successfully linked human and natural system with climate-change and human drivers using Integrated Assessment Model, for basin management. Using Pegasus, a Scientific Workflow Managemen...
Anthropogenic climate change could adversely affect water quality in Lake Champlain from more frequent and more intense flooding events in Lake Champlain Basin as well as reduced ice cover internally in the lake system. Concern within the Lake Champlain system arises from the continued eutrophication of shallow bays such as Missisquoi Bay and the S...
Measuring The Climate Change Impact on Water Quality Using a Weather Generator Pegasus Workflow. In continuation of the ongoing efforts to understanding the climate change impact on Lake Champlain basin, we present the current status: Our previous efforts have successfully linked human and natural system with climate-change and human drivers using...
Dr. Hamed presentation titled 'Modeling the impacts of climate change on water quality in Lake Champlain: Design of an integrated assessment model using Pegasus scientific workflow' presented at the 2014 Vermont Monitoring Cooperative and Mt. Mansfield science and stewardship conference in Burlington, VT.
Climate change is one of this century’s greatest unbalancing forces that affect our planet. Mining the public awareness is an essential step towards the assessment of current climate policies, dedication of sufficient resources, and construction of new policies for business planning. In this paper, we present an exploratory data mining method that...
Climate change is one of this century’s greatest unbalancing forces that affect our planet. Mining the public awareness is an essential step towards the assessment of current climate policies, dedication of sufficient resources, and construction of new policies for business planning. In this paper, we present an exploratory data mining method that...
The Research on Adaptation to Climate Change (RACC) scientists study the Lake Champlain Basin (LCB) as a coupled human and natural system with climate-change and human drivers. In this effort, social scientists, Engineers, and natural scientists collaborate with stakeholders to develop an Integrated Assessment Model (IAModel) for basin management....
Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that describes the task and explains expectations. As social media has exploded in popularity, efforts are being made to use social media advertisement for various recruitment purposes. There are, ho...
Can keyword-hashtag networks, derived from Big Data environments such as Twitter, yield clinicians a powerful tool to extrapolate patterns that may lead to development of new medical therapy and/or drugs? In our paper, we present a systematic network mining method to answer this question. We present HashnetMiner, a new pattern detection algorithm t...
Social Media Big Data have transformed the scale of exploratory analysis on the web and offered new means of performing tasks that were not feasible before. Over a half century ago, Milgram showed that the average number of intermediaries (called the ``degrees of separation'') between two individuals is less than six (between 4.4 and 5.7). The stud...
The emergence of social media has impacted the way people think, communicate, behave, learn, and conduct research. In recent years, a large spectrum of studies has irrupted to analyze and model the social phenomena in correspondence. Driven by the need of commercial interest, providing various services, and the overall necessity of solving social p...
Social Media Big Data have transformed the scale of exploratory analysis on the web and offered new means of performing tasks that were not feasible before. Over a half century ago, Milgram showed that the average number of intermediaries (called the ``degrees of separation'') between two individuals is less than six (between 4.4 and 5.7). The stud...
Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that describes the task and explains expectations. As social media has exploded in popularity, efforts are being made to use social media to recruit for new career opportunities. Particularly, Linked...
We introduce our initial work for developing a social networks recommender system called T-Recs. The system is a time-aware Twitter-based alternative medicine recommender system. We collected a set of tweets (around 500,000 tweets) that contain specific hashtags (#throwingup, #headache, #itching etc) for a three consecutive weeks. The individual tw...
This paper presents a novel architecture that brings together Information Extraction (IE) with Event Processing (EP)research areas to globally monitor human activities and biodiversity dynamics and measure their impact on ecosystems. The two areas (IE and EP) are rich on their own and we believe their integration will achieve a much more comprehens...
We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: 1) the lightweight Variable Trigonometric Threshold (VTT) linear classifier we successfully i...
Questions
Questions (17)
As a continuation of our previous publication titled: The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation, our project is in need of a pharmaceutical domain expert. The main contribution is to validate the computational results and interpret the findings. If this is something that interests you, feel free to reply to me with the best way to contact you.
Much appreciated,
--Dr/Hamed
I have a network problem that I believe would be represented as an adjacency-list on a quantum circuit. Typically, the list is up for traversing from various perspectives (e.g., shortest-path between two points).
Any insight will be much appreciated!
Only serious answers that contribute to the question please would be very much appreciated.
Adjacency-list example:
x-> a, b, c
y-> a, d, e
x-> b, c, d
I am unclear on how to input data into a quantum algorithm using the quantum gate model. I understand that if we need to process 2^n states, then we need n-Qubit. For example, the following 4 states (00, 01, 10, 11) require 2 Qubits, and the following 8 states of (000, 001, ..., 111) require 3 Qubits. Now, if we have a fairly large list with millions of of item, ( e.g., a network of people), using the quantum gate model, how to input these item to the algorithm for processing? Please feel free to discuss in detail. Thanks!
Looking for the French version of PubMed. Let me know if such a resource exists. Thanks in Advance. Genuine answers as much appreciated!
-Ahmed
Hello scholars,
Has anyone had a chance to visualize a multilayered network from a CSV data? I am open to Python, R, Java or whatever.
Thanks in advance!
In your own words: what do you think of the impact of climate change?
-Ahmed
Hello,
I am looking for a reference similar in ways to the Top 10 Data Mining Algorithms but specifically sentiment analysis (Top 10 sentiment analysis algorithms??)
If you know such a reference, I would very much appreciate a pointer to it.
Sincerely,
-Ahmed
Projects
Projects (5)
Drug Repurposing is our only hope as a short term solution before the development of new vaccines. The purpose here is to identify existing drugs that would potentially alleviate COVID-19 symptoms or treat them entirely.
Cancer patients suffer side-effects such as losing hair, nail or skin under the chemotherapy treatment. Here we aim to identify some of such insights hoping it can be further explored as drug-discovery hypotheses that can perhaps be tested in a lab.
Pharmaceutical scientists often search databases of therapeutic molecules to answer a set of drug discovery queries. In this project, we present a novel algorithm called MolecRank, that is a molecule ranking mechanism. The algorithm traverses a network of biological features (e.g., therapeutic molecules, genes, protein, chemical compounds, cell-type, RNA, disease name, etc.) extracted from publications (i.e., article abstracts).
