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<!DOCTYPE HTML>
<html lang="en">
<head>
<meta content="text/html; charset=UTF-8" http-equiv="Content-Type">
<title>Abdurrahman Abul-Basher</title>
<meta content="Abdurrahman Abul-Basher" name="author">
<meta content="width=device-width, initial-scale=1" name="viewport">
<link href="stylesheet.css" rel="stylesheet" type="text/css">
<link href="images/seal_icon.png" rel="icon" type="images/png">
</head>
<body>
<table style="width:100%; max-width:800px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr align="center" style="padding:0px">
<td>
<a href="images/abdurrahman.jpg" target="_blank">
<img alt="profile photo" class="hoverZoomLink"
src="images/abdurrahman_circle.jpg" style="width:40%;max-width:40%;">
</a>
</td>
</tr>
<tr align="center" style="padding:0px">
<td>
<p style="text-align:center">
<a href="https://www.linkedin.com/in/arbasher/" target="_blank"><img alt="Linkedin"
href="https://www.linkedin.com/in/arbasher/"
src="images/Linkedin.png"
style="width:3%"></a>  
<a href="https://scholar.google.com/citations?hl=en&user=0IPfHrwAAAAJ&view_op=list_works&sortby=pubdate"
target="_blank"><img alt="Scholar" src="images/Google_Scholar.png" style="width:3%"></a>  
<a href="https://github.com/arbasher" target="_blank"><img alt="GitHub" src="images/GitHub.png"
style="width:3%"></a>  
<a href="https://twitter.com/meiarbasher" target="_blank"><img alt="Twitter" src="images/Twitter.png"
style="width:3%"></a>  
<a href="mailto:[email protected]" target="_blank"><img alt="Email" src="images/email.svg"
style="width:3%"></a>  
<a href="data/resume.pdf" target="_blank"><img alt="CV" src="images/download.png" style="width:3%"></a>
</p>
<p style="text-align:center">
<name style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 20pt;">
Abdurrahman Abul-Basher
</name>
<br><br>
<name style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 14pt; color:gray;">
Research Fellow
</name>
<br>
<name style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 12pt; color:gray;">
Bioinformatics & Applied Machine Learning Scientist
</name>
</p>
<p style="text-align:center">
<a href="https://hms.harvard.edu/" target="_blank"><img alt="Scholar" src="images/HarvardMS-BCH-Logo.png" style="width:50%"></a>
</p>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 11pt; color:gray;">
Jump to: <a href="#news"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:11pt;color:steelblue;">News</a>
| <a href="#teaching"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:11pt;color:steelblue;">Teachings</a>
| <a href="#paper"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:11pt;color:steelblue;">Research
Articles</a>
</p>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:#2E2E2E; text-align:justify; indent-text: 5em;line-height: 1.5;">
I am a research fellow at <a href="https://research.childrenshospital.org/kwonmoo-lee/" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:steelblue;" target="_blank">Lee Laboratory</a> at <a href="https://hms.harvard.edu/" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:steelblue;" target="_blank">Harvard Medical School</a> and <a href="https://www.childrenshospital.org/" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:steelblue;" target="_blank">Boston Children's Hospital</a>. I work in analyzing cell phenotypic transition dynamics from live-cell images and high-dimensional gene/protien expression data (e.g., transcriptomics, proteomics, and spatial transcriptomics) across human tissues. I am also expert in analyzing large-scale genomics data using cutting edge machine/deep learning algorithms (e.g., contrastive analysis).
</p>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:#2E2E2E; text-align:justify; indent-text: 5em;line-height: 1.5;">
I obtained my PhD in <a
href="https://en.wikipedia.org/wiki/Bioinformatics"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:steelblue;"
target="_blank">Bioinformatics</a>
(an interdisciplinary field) from the University of British Columbia (<a href="https://www.ubc.ca/" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:16px;color:steelblue;" target="_blank">UBC</a>), where I was advised by Dr. Steven J. Hallam (<a
href="https://hallam.microbiology.ubc.ca/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:16px;color:steelblue;"
target="_blank">Hallam Lab</a>). Previously, I obtained my bachelor's in computer
science from King AbdulAziz University (<a href="https://www.kau.edu.sa/home_ENGLISH.aspx"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:16px;color:steelblue;"
target="_blank">KAU</a>) and masters in
information systems security from <a href="https://www.concordia.ca/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:16px;color:steelblue;"
target="_blank">Concordia University</a>, where I
worked with <a href="http://dmas.lab.mcgill.ca/fung/index.htm"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:16px;color:steelblue;"
target="_blank">Dr. Benjamin C. M.
Fung</a> in the <a href="http://dmas.lab.mcgill.ca/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:16px;color:steelblue;"
target="_blank">Data Mining and
Security (DMaS) Lab</a> to discover topics from chat logs for crime investigation.
</p>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; text-align: left;">
<u> Misc:</u> In my spare time, I enjoy reading novels, history, modern philosophy, and writing poetry.</li>
</p>
</td>
</tr>
<tr style="padding:0px">
<td style="padding:0px">
<table align="center" border="0" cellpadding="20" cellspacing="0" width="100%">
<tbody>
<tr>
<td style="width: 50%;vertical-align:top">
<heading
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
Research
</heading>
<br>
<ul style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; text-align: left;line-height: 1.5">
<li>Live cell image analysis</li>
<li>Single-cell analysis</li>
<li>Microbiome multiomics data analysis</li>
<li><a href="pathpred.html"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Metabolic
pathway prediction</a></li>
<li>Pathway differential and enrichment analysis</li>
<li><a href="mllearning.html"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Multi-label
classification</a></li>
<li>Network analysis and graph learning</li>
</ul>
</td>
<td style="width: 55%;vertical-align:top">
<heading
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
Education
</heading>
<br>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; text-align: left;line-height: 1.5">
PhD in Bioinformatics, 2020
<br>
<a style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; color:steelblue"
href="https://www.ubc.ca/" target="_blank">
The University of British Columbia (UBC)</a>
<br><br>
Master of Applied Science in Information Systems Security, 2011
<br>
<a style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; color:steelblue"
href="https://www.concordia.ca/" target="_blank">Concordia University</a>
<br><br>
BSc in Computer Science, 2008
<br>
<a style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:12pt; color:steelblue"
href="https://www.kau.edu.sa/home_ENGLISH.aspx" target="_blank">King AbdulAziz University
(KAU)</a>
<br>
</p>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
<tr style="padding:0px">
<td style="padding:0px">
<table align="left" border="0" cellpadding="20" cellspacing="0" width="100%">
<tbody>
<tr>
<td style="vertical-align:middle">
<heading
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
Selected projects
</heading>
</td>
<td>
<table align="center" border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody>
<tr>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="phet" src="images/software_icons/phet.png" style="width:50%">
<br>
<a href="https://github.com/kleelab-bch/phet" target="_blank">
<papertitle>PHet</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="pride" src="images/software_icons/pride.png" style="width:50%">
<br>
<papertitle>pride (coming)</papertitle>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="mlts" src="images/software_icons/mlts.png" style="width:50%">
<br>
<papertitle>mltS (coming)</papertitle>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="leads" src="images/software_icons/leads.png" style="width:50%">
<br>
<a href="https://github.com/hallamlab/leADS" target="_blank">
<papertitle>leADS</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="triumpf" src="images/software_icons/triumpf.png" style="width:50%">
<br>
<a href="https://github.com/hallamlab/triUMPF" target="_blank">
<papertitle>triUMPF</papertitle>
</a>
</td>
</tr>
<tr>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="pathway2vec" src="images/software_icons/pathway2vec.png"
style="width:50%">
<br>
<a href="https://github.com/hallamlab/pathway2vec" target="_blank">
<papertitle>pathway2vec</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="mllr" src="images/software_icons/mllr.png" style="width:50%">
<br>
<a href="https://github.com/hallamlab/mlLGPR" target="_blank">
<papertitle>mlLGPR</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="remap" src="images/software_icons/remap.png" style="width:50%">
<br>
<a href="https://github.com/hallamlab/reMap" target="_blank">
<papertitle>reMap</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="prepBioCyc" src="images/software_icons/prepBioCyc.png" style="width:50%">
<br>
<a href="https://github.com/arbasher/prepBioCyc" target="_blank">
<papertitle>prepBioCyc</papertitle>
</a>
</td>
<td style="padding:5px;width:20%;vertical-align:middle">
<img alt="strasplit" src="images/software_icons/straSplit.png" style="width:50%">
<br>
<a href="https://github.com/arbasher/straSplit" target="_blank">
<papertitle>straSplit</papertitle>
</a>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
<tr style="padding:0px">
<td style="padding:0px">
<table align="left" border="0" cellpadding="20" cellspacing="0" width="100%">
<tbody>
<tr>
<td style="width: 100%;vertical-align:top">
<heading
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
Selected fellowships and awards
</heading>
<br>
<ul style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:15px;color:#151515;line-height: 1.5">
<li>Four Year Fellowships (4YF) ($18,200 per year + tuition fee), The University of British
Columbia (UBC), Canada. 2013-2017.
</li>
<li>Faculty of Science - Graduate Support Initiative (GSI) Fund ($8,500 per year), The
University of British Columbia (UBC), Canada.2013-2017.
</li>
<li>Power Corporation of Canada Graduate Fellowships ($5,000), Concordia University, Canada.
2009-2010.
</li>
<li>Concordia Graduate Student Support Program (GSSP) ($15,000 per year), Concordia
University, Canada. 2009-2011.
</li>
<li>First Honor Graduate for graduating with high GPA from King AbdulAziz University, Saudi
Arabia. 2008.
</li>
</ul>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
<tr style="padding:0px">
<td>
<heading id="news"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
News
</heading>
<br>
<table align="left" border="0" cellspacing="0" width="60%">
<tbody style="display: inline-block; border: 1px #2E2E2E; max-height: 500px; overflow-y: scroll; vertical-align: top">
<tr>
<td>
<ul style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:15px;color:#151515;line-height: 1.5">
<li>Pleased to announce that our abstract "Heterogeneity-Preserving Discriminative Feature Selection for Subtype Discovery" got accepted at <a href="https://www.cell-symposia.com/conceptual-single-cells-2023/default.asp" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Cell Symposia: The conceptual power of single cell biology</a>, conference, 2023.
</li>
<li> Pleased to announce that our abstract "Hetero-Discriminative preserving feature selection for subtype discovery" got accepted for Dr. M. Judah Folkman Research Day at <a href="https://www.childrenshospital.org/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Boston Children's Hospital</a>, 2023.
</li>
<li>I gave an invited talk at <a href="https://www.childrenshospital.org/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Boston Children's Hospital</a>, 2022.
</li>
<li> Pleased to announce that our paper <a href="data/chap.pdf" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Aggregating statistically correlated metabolic pathways into groups to improve prediction performance</a> got accepted at BIOINFORMATICS, 2022.
</li>
<li>Our paper <a href="https://www.biorxiv.org/content/10.1101/2020.08.21.260109v2" style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Relabeling metabolic pathway data with groups to improve prediction outcomes</a> got accepted at ICCABS, 2021.
</li>
<li>I gave an invited talk at <a href="https://moffitt.org/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">H. Lee Moffitt Cancer Center & Research Institute</a>, 2021.
</li>
<li>I gave an invited talk at <a href="https://www.childrenshospital.org/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Boston Children's Hospital</a>, Harvard Medical School, Harvard University, 2021.
</li>
<li> Pleased to announce that the source code for <a
href="https://github.com/hallamlab/leADS"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">leADS</a>
is publicly made available!
</li>
<li> Pleased to hear that our article <a
href="https://www.liebertpub.com/doi/abs/10.1089/cmb.2021.0258?journalCode=cmb"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Metabolic
pathway prediction using non-negative matrix factorization with improved precision</a>
has been accepted at the Journal of computational biology (JCB), 2021!
</li>
<li>I gave an invited talk at <a href="https://cpd.dana-farber.org/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Center
for Protein Degradation at Dana-Farber Cancer Institute</a>, Harvard Medical School,
Harvard University, 2021.
</li>
<li>I'm happy to announce that I've received the <strong>President’s Academic Excellence
Initiative PhD Award</strong>, The University of British Columbia (UBC), 2020!
</li>
<li>I gave a presentation at the 10th International Conference on Computational Advances in
Bio and medical Sciences (<a href="https://iccabs.engr.uconn.edu/2020/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">ICCABS</a>),
2020.
</li>
<li>Our paper <a href="https://link.springer.com/chapter/10.1007/978-3-030-79290-9_4"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Metabolic
pathway prediction using non-negative matrix factorization with improved precision</a>
got accepted at ICCABS, 2020.
</li>
<li>Our paper <a href="https://academic.oup.com/bioinformatics/article/37/6/822/5932372"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Leveraging
heterogeneous network embedding for metabolic pathway prediction</a> got accepted at
Bioinformatics, 2020.
</li>
<li>Our paper <a
href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008174"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">Metabolic
pathway inference using multi-label classification with rich pathway features</a> got
accepted at PLOS Computational Biology, 2020.
</li>
</ul>
</td>
</tr>
</tbody>
</table>
<table border="0" cellspacing="0">
<tbody style="display: inline-block; border: 1px #2E2E2E; max-height: 500px; overflow-y: scroll; vertical-align: top">
<tr>
<td>
<a class="twitter-timeline" data-width="299" data-theme="light" data-chrome="nofooter noborders" href="https://twitter.com/meiarbasher?ref_src=twsrc%5Etfw">
Tweets by @meiarbasher
</a>
<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
</td>
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<td>
</tr>
<tr style="padding:0px">
<td style="padding:2.5%">
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr style="padding:0px">
<td>
<p id="teaching" style="text-align:left;">
<name style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 30pt;">
Teachings
</name>
</p>
</td>
</tr>
<tr>
<td valign="center">
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:14pt;color:#2E2E2E">
The University of British Columbia, Master of Data Sciences (<a
href="https://masterdatascience.ubc.ca/"
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif;font-size:12pt;color:steelblue;">MDS</a>)
</p>
<ul style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:15px;color:#151515;line-height: 1.2">
<li> Graduate Student Instructor, DSCI 571 Supervised Learning I, 2016</li>
<li> Graduate Student Instructor, DSCI 573 Feature and Model Selection, 2017</li>
<li> Graduate Student Instructor, DSCI 575 Advanced Machine Learning, 2017</li>
</ul>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
<tr style="padding:0px">
<td style="padding:0px">
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;">
<tbody>
<tr style="padding:0px">
<td style="padding:2.5%;width:63%">
<p id="paper" style="text-align:left;">
<name style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 30pt;">
Selected publications
</name>
</p>
<p style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size: 20px;color:#424242; ">
<span style="background-color:#D4F5CE;">
published
</span>
<span style="background-color:#8CB3F4;">
accepted
</span>
<span style="background-color:#F5F79D;">
preprint
</span>
<span style="background-color:#F2CEF5;">
under preparation
</span>
<span style="color:#FFFFFF; background-color:#65397C;">
under review
</span>
</p>
</td>
</tr>
</tbody>
</table>
<table style="width:100%; margin-right:auto;margin-left:auto;border:0px;border-spacing:0px;border-collapse:separate;">
<tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="PHet" src="images/phet.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #F2CEF5">
<a target="_blank">
<papertitle>Heterogeneity-Preserving Discriminative Feature Selection for Subtype Discovery
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong>,
<a href="https://www.linkedin.com/in/calebhallinan/" target="_blank"> Caleb Hallinan</a>,
and
<a href="https://connects.catalyst.harvard.edu/Profiles/display/Person/7821"
target="_blank">Kwonmoo Lee</a>
<br>
<em>Under preparation</em>, 2024
<br>
<a href="https://github.com/kleelab-bch/phet" target="_blank">code</a>
<br><br>
<paperbody>
In this article, we present a novel approach, termed PHet (Preserving Heterogeneity), designed to capture the diversity within each disease condition while maintaining the discrimination of known disease states. Our analysis identified features with significant differences in interquartile range (IQR) between classes, indicating crucial subtype information. Validation using public single-cell RNA-seq and microarray datasets demonstrated PHet's effectiveness in preserving sample heterogeneity while maintaining discrimination of known disease/cell states, surpassing the performance of previous outlier-based methods.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="mltS" src="images/mlts.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #F2CEF5">
<a target="_blank">
<papertitle>Leveraging multiple (less-trusted) sources to improve metabolic pathway
prediction [TO BE ADDED]
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong>,
<a> XXXX </a>
<br>
<em>Under preparation</em>, 2024
<br>
<a target="_blank">[TO BE ADDED]</a>
<br><br>
<paperbody>
This paper presents mltS (multi-label learning based on less-trusted sources) which is an
ensemble based learning that leverages the idea of estimating memebers reliability scores in
an ensemble given a small reference collection dataset. Using mltS, one can the assess the
reliability of each model while performing inference in three ways: "meta-predict (mp)",
"meta-weight (mw)", and "meta-adaptive (ma)".
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="leADS" src="images/leads.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #65397C">
<a href="https://doi.org/10.1101/2020.09.14.297424" target="_blank">
<papertitle>leADS: improved metabolic pathway inference based on active dataset
subsampling
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong>,
<a href="https://www.linkedin.com/in/aditi-nagaraj-195389176/" target="_blank">Aditi N.
Nallan</a>,
<a href="https://www.linkedin.com/in/ryan-mclaughlin-725b09117/" target="_blank">Ryan J.
McLaughlin</a>,
<a href="https://www.linkedin.com/in/julia-anstett-105b6a35/" target="_blank">Julia Anstett</a>,
and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>Under review</em>, 2024
<br>
<a href="https://github.com/hallamlab/leADS" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents leADS (multi-label learning based on active dataset subsampling) that
leverages the idea of subsampling examples from a pool of multi-label data to reduce the
negative impact of training loss.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="CHAP" src="images/chap.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #8CB3F4">
<a href="data/chap.pdf" target="_blank">
<papertitle>
Aggregating statistically correlated metabolic pathways into groups to improve prediction performance
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong> and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>BIOINFORMATICS (to appear)</em>, 2022
<br>
<a href="https://github.com/hallamlab/chap" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents the CHAP (correlated pathway group) package comprising of three hierarchical mixture models: SOAP (sparse correlated pathway group, SPREAT (distributed sparse correlated pathway group), and CTM (correlated topic model) to characterize pathways.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="reMap" src="images/remap.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #8CB3F4">
<a href="https://doi.org/10.1101/2020.08.21.260109" target="_blank">
<papertitle>Relabeling metabolic pathway data with groups to improve prediction outcomes</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong> and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>ICCABS (to appear)</em>, 2021
<br>
<a href="https://github.com/hallamlab/reMap" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents the reMap framework that performs mapping examples to a different set of labels, characterized as pathway groups, where a group comprises of statistically correlated pathways.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="triUMPF" src="images/triumpf.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #D4F5CE">
<a href="https://doi.org/10.1089/cmb.2021.0258" target="_blank">
<papertitle>Metabolic pathway prediction using non-negative matrix factorization with improved precision
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong>,
<a href="https://www.linkedin.com/in/ryan-mclaughlin-725b09117/" target="_blank">Ryan J.
McLaughlin</a>, and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>Journal of computational biology (JCB)</em>, 2021
<br>
<a href="https://github.com/hallamlab/triUMPF" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents triUMPF (triple non-negative matrix factorization (NMF) with community
detection for metabolic pathway inference) that combines three stages of NMF to capture
myriad relationships between enzymes and pathways within a graph network followed by
community detection to extract higher order structure based on the clustering of vertices
sharing similar statistical properties.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="pathway2vec" src="images/pathway2vec.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #D4F5CE">
<a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa906/5932372"
target="_blank">
<papertitle>Leveraging heterogeneous network embedding for metabolic pathway prediction
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong> and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>Bioinformatics</em>, 2020
<br>
<a href="https://github.com/hallamlab/pathway2vec" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents pathway2vec, a software package consisting of six representational
learning based modules used to automatically generate features for pathway inference.
</paperbody>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<img alt="mlLGPR" src="images/mllr.png" style="width:100%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle; border-bottom:2px solid #D8D8D8; border-right:10px solid #D4F5CE">
<a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008174"
target="_blank">
<papertitle>Metabolic pathway inference using multi-label classification with rich pathway features
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong>,
<a href="https://www.linkedin.com/in/ryan-mclaughlin-725b09117/" target="_blank">Ryan J.
McLaughlin</a>, and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>PLOS Computational Biology</em>, 2020
<br>
<a href="https://github.com/hallamlab/mlLGPR" target="_blank">code</a>
<br><br>
<paperbody>
This paper presents mlLGPR (multi-label logistic regression for pathway prediction)
framework that uses supervised multi-label classification and rich pathway features to infer
metabolic networks at the individual, population and community levels of organization.
</paperbody>
</td>
</tr>
</tbody>
</table>
</td>
</tr>
<tr style="padding:0px">
<td style="padding:0px">
<table align="left" border="0" cellpadding="20" cellspacing="0" width="100%">
<tbody>
<tr>
<td style="vertical-align:top">
<heading
style="font-family: Montserrat,'Lucida Sans', 'Lucida Sans Regular', 'Lucida Grande', 'Lucida Sans Unicode', Geneva, Verdana, sans-serif; font-size:28px;color:#2E2E2E">
Posters
</heading>
</td>
</tr>
</tbody>
</table>
<table style="width:100%; margin-right:auto;margin-left:auto;border:0px;border-spacing:0px;border-collapse:separate;">
<tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle;font-family:Arial;font-size:28px;">
<img alt="cmde" src="images/cmde.png" style="width:70%">
</td>
<td style="padding:20px;width:75%;vertical-align:middle;">
<a href="data/cmde.pdf" target="_blank">
<papertitle>Machine Learning Approach to Recovering Metabolic Pathways from Metagenomics Sequences
</papertitle>
</a>
<br>
<strong>Abdurrahman Abul-Basher</strong> and
<a href="https://www.linkedin.com/in/steven-hallam-58b5538b/?originalSubdomain=ca"
target="_blank">Steven J. Hallam</a>
<br>
<em>CMDE</em>, 2016
</td>
</tr>
</tbody>
</table>
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