{"id":28,"date":"2023-08-23T22:36:40","date_gmt":"2023-08-24T02:36:40","guid":{"rendered":"https:\/\/carleton.ca\/dehne\/?page_id=28"},"modified":"2025-12-27T09:49:08","modified_gmt":"2025-12-27T14:49:08","slug":"research","status":"publish","type":"page","link":"https:\/\/carleton.ca\/dehne\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<h3>Research Interests<\/h3>\n<ul>\n<li>data science<\/li>\n<li>parallel algorithms<\/li>\n<li>cloud computing<\/li>\n<li>multi-core processors and GPUs<\/li>\n<li>bioinformatics<\/li>\n<li>business data analytics<\/li>\n<li>computational engineering<\/li>\n<\/ul>\n<hr \/>\n<h3 style=\"text-align: center;\">Project Examples<\/h3>\n<hr \/>\n<h4 class=\"CjVfdc\"><span class=\"C9DxTc \">Bioinformatics<\/span><\/h4>\n<p class=\"zfr3Q CDt4Ke \" dir=\"ltr\"><span class=\"C9DxTc \">Together with Professor Ashkan Golshani from the Institute for Biochemistry, Professor Dehne leads an interdisciplinary research group on computational <a href=\"https:\/\/en.wikipedia.org\/wiki\/Proteomics\" target=\"_blank\" rel=\"noopener noreferrer\">proteomics<\/a> and computational <a href=\"https:\/\/en.wikipedia.org\/wiki\/Drug_design\" target=\"_blank\" rel=\"noopener noreferrer\">drug design<\/a>. The group developed the first high-performance computing system (named PIPE) for high-precision <a href=\"https:\/\/en.wikipedia.org\/wiki\/Protein%E2%80%93protein_interaction\" target=\"_blank\" rel=\"noopener noreferrer\">protein to protein interaction<\/a> prediction and the design of new <a href=\"https:\/\/en.wikipedia.org\/wiki\/Peptide_synthesis\" target=\"_blank\" rel=\"noopener noreferrer\">synthetic peptides<\/a> with specific interaction properties. Their computational method is based on a novel <a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\" target=\"_blank\" rel=\"noopener noreferrer\">machine learning<\/a> algorithm that utilizes in-depth knowledge from experimental protein to protein interaction detection results in Professor Golshani\u2019s lab. PIPE has won international acclaim and has enabled new biomedical research. Professors Dehne and Golshani collaborated with the Ottawa Hospital Research Institute on new synthetic peptides for <a href=\"https:\/\/en.wikipedia.org\/wiki\/Muscular_dystrophy\" target=\"_blank\" rel=\"noopener noreferrer\">muscular dystrophy<\/a> stem cell therapy; with the Department of Biochemistry at the University of Regina on designing anti <a href=\"https:\/\/en.wikipedia.org\/wiki\/Zika_virus\" target=\"_blank\" rel=\"noopener noreferrer\">Zika virus<\/a> peptides; with the School of Medicine at WITS University in Johannesburg on new methods to explain <a href=\"https:\/\/en.wikipedia.org\/wiki\/Evolutionary_transition_in_individuality\" target=\"_blank\" rel=\"noopener noreferrer\">evolutionary transitions<\/a>; and with Agriculture Canada on the development of new <a href=\"https:\/\/en.wikipedia.org\/wiki\/Soybean\" target=\"_blank\" rel=\"noopener noreferrer\">soy bean<\/a> plants that withstand cold climates. In collaboration with the Ottawa Hospital Research Institute and the Department of Biochemistry at the University of Regina, Professors Dehne and Golshani designed, via large-scale computation, a new synthetic peptide to block the interaction between the <a href=\"https:\/\/en.wikipedia.org\/wiki\/Coronavirus_spike_protein\" target=\"_blank\" rel=\"noopener noreferrer\">COVID spike protein<\/a> and the human <a href=\"https:\/\/en.wikipedia.org\/wiki\/Angiotensin-converting_enzyme_2\" target=\"_blank\" rel=\"noopener noreferrer\">ACE2 receptor<\/a>. The goal is to design a new drug for treating COVID patients in the hospital. Their novel peptide was synthesized and tested at the Ottawa Hospital Research Institute and the National Microbiology Laboratory in Winnipeg (on live COVID viruses). Both lab tests were successful.<\/span><\/p>\n<p dir=\"ltr\">Professors Dehne and Golshani founded a biotech company, <a href=\"https:\/\/designedbiologics.com\/\" target=\"_blank\" rel=\"noopener noreferrer\">Designed Biologics Inc<\/a>, that uses AI to design peptides with custom targeting properties for therapeutics.<\/p>\n<h3><\/h3>\n<h4 id=\"h.6n68uholpuro\" class=\"GV3q8e yMxPgf aP9Z7e\">Business Data Analytics<\/h4>\n<p class=\"zfr3Q CDt4Ke \" dir=\"ltr\"><span class=\"C9DxTc \">Professor Dehne is interested in interdisciplinary research projects that involve large data sets and computationally hard problems. One such example is large scale <a href=\"https:\/\/en.wikipedia.org\/wiki\/Business_analytics\" target=\"_blank\" rel=\"noopener noreferrer\">business data analytics<\/a>. When <a href=\"https:\/\/en.wikipedia.org\/wiki\/IBM\" target=\"_blank\" rel=\"noopener noreferrer\">IBM<\/a> purchased Cognos Corporation in Ottawa, they established Ottawa as IBM\u2019s main centre for data analytics in Canada. For large scale data systems of corporate clients, IBM encountered technical difficulties because their software tools had <a href=\"https:\/\/en.wikipedia.org\/wiki\/Computer_performance\" target=\"_blank\" rel=\"noopener noreferrer\">performance<\/a> issues on large data sets. That lead to discussions between IBM and Prof. Dehne&#8217;s research lab at Carleton University. The data analytics operations that created the performance issues were complex aggregate <a href=\"https:\/\/en.wikipedia.org\/wiki\/Group_by_(SQL)\" target=\"_blank\" rel=\"noopener noreferrer\">group-by queries<\/a> on large data sets, with the additional challenge that those data sets were highly dynamic. IBM funded a research project in Prof. Dehne&#8217;s lab to address this problem. Their solution and delivered prototype won an <a href=\"https:\/\/casweb.59b0587b.public.multi-containers.ibm.com\/ibm\/cas\/canada\/awards\" target=\"_blank\" rel=\"noopener noreferrer\">IBM Innovation Impact Of The Year Award<\/a>, and Prof. Dehne was appointed <a href=\"https:\/\/www.ibm.com\/ibm\/cas\/canada\" target=\"_blank\" rel=\"noopener noreferrer\">Fellow of the IBM Centre For Advanced Studies<\/a> in Toronto, Canada.<\/span><\/p>\n<h3><\/h3>\n<h4 id=\"h.ghjt9fnii4xh\" class=\"GV3q8e yMxPgf aP9Z7e\">Computational Welding Mechanics<\/h4>\n<p class=\"zfr3Q CDt4Ke \" dir=\"ltr\"><span class=\"C9DxTc aw5Odc \">Computational welding mechanics<\/span><span class=\"C9DxTc \">\u00a0is about the precise simulation of welding processes with the goal of controlling <a href=\"https:\/\/en.wikipedia.org\/wiki\/Robot_welding\" target=\"_blank\" rel=\"noopener noreferrer\">welding robots<\/a> to perform complex welding tasks. The field was pioneered by\u00a0<\/span><a class=\"XqQF9c\" href=\"https:\/\/carleton.ca\/mae\/profile\/john-a-goldak\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span class=\"C9DxTc aw5Odc \">Professor John Goldak<\/span><\/a><span class=\"C9DxTc \">\u00a0who is also the principal author of the eminent\u00a0<\/span><a class=\"XqQF9c\" href=\"https:\/\/link.springer.com\/book\/10.1007\/b101137\" target=\"_blank\" rel=\"noopener noreferrer\"><span class=\"C9DxTc aw5Odc \">book<\/span><\/a><span class=\"C9DxTc \">. The computations are extremely complex and time consuming. Prof. Dehne collaborated with Prof. Goldak on how to parallelize his welding simulation algorithms and execute them on arrays of <a href=\"https:\/\/en.wikipedia.org\/wiki\/Graphics_processing_unit\" target=\"_blank\" rel=\"noopener noreferrer\">GPU<\/a>s (e.g. five GPUs with 4,000 processor cores each). That enabled Prof. Goldak to greatly improve the speed and precision of his welding simulations, leading to the commercial development of new real-time, high precision, multi-GPU control units for <\/span><span class=\"C9DxTc aw5Odc \">welding robots<\/span><span class=\"C9DxTc \">. These control units are now routinely used by Canadian oil companies for robotic welding of <a href=\"https:\/\/en.wikipedia.org\/wiki\/Pipeline\" target=\"_blank\" rel=\"noopener noreferrer\">oil pipelines<\/a>.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Research Interests data science parallel algorithms cloud computing multi-core processors and GPUs bioinformatics business data analytics computational engineering Project Examples Bioinformatics Together with Professor Ashkan Golshani from the Institute for Biochemistry, Professor Dehne leads an interdisciplinary research group on computational proteomics and computational drug design. The group developed the first high-performance computing system (named PIPE) [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Research - Professor Frank Dehne<\/title>\n<meta name=\"description\" content=\"Research Interests data science parallel algorithms cloud computing multi-core processors and GPUs bioinformatics business data analytics computational\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/carleton.ca\/dehne\/research\/\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/carleton.ca\/dehne\/research\/\",\"url\":\"https:\/\/carleton.ca\/dehne\/research\/\",\"name\":\"Research - 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