Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Faria-Campos BMCBioinformatics2015 16-S19.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Clay CancerInformatics2017 16.png|240px]]</div>
'''"[[Journal:FluxCTTX: A LIMS-based tool for management and analysis of cytotoxicity assays data|FluxCTTX: A LIMS-based tool for management and analysis of cytotoxicity assays data]]"'''
'''"[[Journal:Bioinformatics education in pathology training: Current scope and future direction|Bioinformatics education in pathology training: Current scope and future direction]]"'''


Cytotoxicity assays have been used by researchers to screen for cytotoxicity in compound libraries. Researchers can either look for cytotoxic compounds or screen "hits" from initial high-throughput drug screens for unwanted cytotoxic effects before investing in their development as a pharmaceutical. These assays may be used as an alternative to animal experimentation and are becoming increasingly important in modern laboratories. However, the execution of these assays in large-scale and different laboratories requires, among other things, the management of protocols, reagents, and cell lines used, as well as the data produced, which can be a challenge. The management of all this information is greatly improved by the utilization of computational tools to save time and guarantee quality. However, a tool that performs this task designed specifically for cytotoxicity assays is not yet available.
Training [[Anatomical pathology|anatomic]] and [[clinical pathology]] residents in the principles of [[bioinformatics]] is a challenging endeavor. Most residents receive little to no formal exposure to bioinformatics during medical education, and most of the pathology training is spent interpreting [[histopathology]] slides using light microscopy or focused on laboratory regulation, management, and interpretation of discrete [[laboratory]] data. At a minimum, residents should be familiar with data structure, data pipelines, data manipulation, and data regulations within [[Clinical laboratory|clinical laboratories]]. Fellowship-level training should incorporate advanced principles unique to each subspecialty. Barriers to bioinformatics education include the clinical apprenticeship training model, ill-defined educational milestones, inadequate faculty expertise, and limited exposure during medical training. Online educational resources, case-based learning, and incorporation into molecular genomics education could serve as effective educational strategies. Overall, pathology bioinformatics training can be incorporated into pathology resident curricula, provided there is motivation to incorporate institutional support, educational resources, and adequate faculty expertise. ('''[[Journal:Bioinformatics education in pathology training: Current scope and future direction|Full article...]]''')<br />
 
In this work, we have used a workflow based LIMS — [[Satya Sistemas Ltda.#Flux2|the Flux system]] — and the Together Workflow Editor as a framework to develop FluxCTTX, a tool for management of data from cytotoxicity assays performed at different laboratories. ('''[[Journal:FluxCTTX: A LIMS-based tool for management and analysis of cytotoxicity assays data|Full article...]]''')<br />
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''Recently featured'':  
''Recently featured'':  
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Revision as of 16:24, 2 October 2017

Fig1 Clay CancerInformatics2017 16.png

"Bioinformatics education in pathology training: Current scope and future direction"

Training anatomic and clinical pathology residents in the principles of bioinformatics is a challenging endeavor. Most residents receive little to no formal exposure to bioinformatics during medical education, and most of the pathology training is spent interpreting histopathology slides using light microscopy or focused on laboratory regulation, management, and interpretation of discrete laboratory data. At a minimum, residents should be familiar with data structure, data pipelines, data manipulation, and data regulations within clinical laboratories. Fellowship-level training should incorporate advanced principles unique to each subspecialty. Barriers to bioinformatics education include the clinical apprenticeship training model, ill-defined educational milestones, inadequate faculty expertise, and limited exposure during medical training. Online educational resources, case-based learning, and incorporation into molecular genomics education could serve as effective educational strategies. Overall, pathology bioinformatics training can be incorporated into pathology resident curricula, provided there is motivation to incorporate institutional support, educational resources, and adequate faculty expertise. (Full article...)

Recently featured:

FluxCTTX: A LIMS-based tool for management and analysis of cytotoxicity assays data
Bioinformatics: Indispensable, yet hidden in plain sight
Electronic lab notebooks: Can they replace paper?