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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Zakutayev SciData2018 5.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Riley JOfBioEng2017 11.gif|240px]]</div>
'''"[[Journal:An open experimental database for exploring inorganic materials|An open experimental database for exploring inorganic materials]]"'''
'''"[[Implementation and use of cloud-based electronic lab notebook in a bioprocess engineering teaching laboratory|Implementation and use of cloud-based electronic lab notebook in a bioprocess engineering teaching laboratory]]"'''


The use of advanced machine learning algorithms in experimental [[Materials informatics|materials science]] is limited by the lack of sufficiently large and diverse datasets amenable to data mining. If publicly open, such data resources would also enable materials research by scientists without access to expensive experimental equipment. Here, we report on our progress towards a publicly open High Throughput Experimental Materials (HTEM) Database (htem.nrel.gov). This database currently contains 140,000 sample entries, characterized by structural (100,000), synthetic (80,000), chemical (70,000), and optoelectronic (50,000) properties of inorganic thin film materials, grouped in >4,000 sample entries across >100 materials systems; more than a half of these data are publicly available. This article shows how the HTEM database may enable scientists to explore materials by browsing web-based user interface and an application programming interface. This paper also describes a HTE approach to generating materials data and discusses the [[laboratory information management system]] (LIMS) that underpins the HTEM database. Finally, this manuscript illustrates how advanced machine learning algorithms can be adopted to materials science problems using this open data resource. ('''[[Journal:An open experimental database for exploring inorganic materials|Full article...]]''')<br />
[[Electronic laboratory notebook]]s (ELNs) are better equipped than paper [[laboratory notebook]]s (PLNs) to handle present-day life science and engineering experiments that generate large data sets and require high levels of data integrity. But limited training and a lack of workforce with ELN knowledge have restricted the use of ELN in academic and industry research [[Laboratory|laboratories]], which still rely on cumbersome PLNs for record keeping. We used [[LabArchives, LLC|LabArchives]], a cloud-based ELN in our bioprocess engineering lab course to train students in electronic record keeping, good documentation practices (GDPs), and [[data integrity]].
 
Implementation of ELN in the bioprocess engineering lab course, an analysis of user experiences, and our development actions to improve ELN training are presented here. ELN improved pedagogy and learning outcomes of the lab course through streamlined workflow, quick data recording and archiving, and enhanced data sharing and collaboration. It also enabled superior data integrity, simplified information exchange, and allowed real-time and remote monitoring of experiments. ('''[[Journal:Implementation and use of cloud-based electronic lab notebook in a bioprocess engineering teaching laboratory|Full article...]]''')<br />
<br />
<br />
''Recently featured'':  
''Recently featured'':  
: ▪ [[Journal:An open experimental database for exploring inorganic materials|An open experimental database for exploring inorganic materials]]
: ▪ [[Journal:Broad-scale genetic diversity of Cannabis for forensic applications|Broad-scale genetic diversity of Cannabis for forensic applications]]
: ▪ [[Journal:Broad-scale genetic diversity of Cannabis for forensic applications|Broad-scale genetic diversity of Cannabis for forensic applications]]
: ▪ [[Journal:Arkheia: Data management and communication for open computational neuroscience|Arkheia: Data management and communication for open computational neuroscience]]
: ▪ [[Journal:Arkheia: Data management and communication for open computational neuroscience|Arkheia: Data management and communication for open computational neuroscience]]
: ▪ [[Journal:Developing a bioinformatics program and supporting infrastructure in a biomedical library|Developing a bioinformatics program and supporting infrastructure in a biomedical library]]

Revision as of 15:51, 11 June 2018

Fig1 Riley JOfBioEng2017 11.gif

"Implementation and use of cloud-based electronic lab notebook in a bioprocess engineering teaching laboratory"

Electronic laboratory notebooks (ELNs) are better equipped than paper laboratory notebooks (PLNs) to handle present-day life science and engineering experiments that generate large data sets and require high levels of data integrity. But limited training and a lack of workforce with ELN knowledge have restricted the use of ELN in academic and industry research laboratories, which still rely on cumbersome PLNs for record keeping. We used LabArchives, a cloud-based ELN in our bioprocess engineering lab course to train students in electronic record keeping, good documentation practices (GDPs), and data integrity.

Implementation of ELN in the bioprocess engineering lab course, an analysis of user experiences, and our development actions to improve ELN training are presented here. ELN improved pedagogy and learning outcomes of the lab course through streamlined workflow, quick data recording and archiving, and enhanced data sharing and collaboration. It also enabled superior data integrity, simplified information exchange, and allowed real-time and remote monitoring of experiments. (Full article...)

Recently featured:

▪ An open experimental database for exploring inorganic materials
▪ Broad-scale genetic diversity of Cannabis for forensic applications
▪ Arkheia: Data management and communication for open computational neuroscience
Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=33408"