55,122 research outputs found
Ms. Courtney Chartier, RWWL AUC, August 2011
No full textThis video is a conversation with Ms. Courtney Chartier. Ms. Chartier talks about her work on the "New Georgia Encyclopedia" and "Online Voter Education Project." Andrea Jackson, AUC Woodruff Library, is the interviewer
Ms. Neely Terrell, RWWL AUC, March 2012
No full textThis video is a conversation with Ms. Neely Terrell. Ms. Terrell talks about her book, "Super Singles Activate". Anthony Kinsey and Jahnesta Horney, AUC Woodruff Library, are the interviewers
sj-docx-2-tct-10.1177_15330338211045496 - Supplemental material for The Clinical Significance of RMI2 in Hepatocellular Carcinoma
No full textSupplemental material, sj-docx-2-tct-10.1177_15330338211045496 for The Clinical Significance of RMI2 in Hepatocellular Carcinoma by Bin Zheng, MS, Heng Wang, MS, Jin-xue Wang, MS, Zheng-hong Liu, MS, Pu Zhang, MD, Dahong Zhang and MD in Technology in Cancer Research & Treatment</p
sj-pdf-1-tct-10.1177_15330338211045496 - Supplemental material for The Clinical Significance of RMI2 in Hepatocellular Carcinoma
No full textSupplemental material, sj-pdf-1-tct-10.1177_15330338211045496 for The Clinical Significance of RMI2 in Hepatocellular Carcinoma by Bin Zheng, MS, Heng Wang, MS, Jin-xue Wang, MS, Zheng-hong Liu, MS, Pu Zhang, MD, Dahong Zhang and MD in Technology in Cancer Research & Treatment</p
Angela Wang Interview
No full textAngela Wang (Class of 2018) was interviewed by Laurence Lundy via the Zoom internet-based video conferencing software on June 16th, 2020. She grew up in the wealthy, white majority Dallas suburb of Flower Mound and attended predominantly white schools. She majored in biochemistry at SMU, where she also became interested in human rights and active in the LGBTQ+ community. Ultimately, Ms. Wang received a Bachelor's of Science and a Bachelor's of Arts in Biochemistry and Human Rights. She had an internship in Chennai, India, with Unite for Sight, where she helped conduct eye exam screenings related to cataracts. During her stay, she was struck by the disparity in wealth and resources between various sectors of Indian society. She also was an intern at the Dallas Area Rape Crisis Center and studied abroad in Thailand. She found friends through Spectrum (an LGBTQ+ group), Mustang Heroes, and the President's Scholars Program, as well as the multicultural sororities and fraternities and the Asian clubs. She discusses the Black@SMU movement, the Trump election, and various examples of what she perceived as SMU's lukewarm approach to addressing racism during her time as a student. At the time of the interview, Ms. Wang was attending UT Southwestern as a graduate student in medicine
LC-MS/MS Data from Analysis of Bacteriochlorophylls
No full textThis data set contains LC-MS/MS analyses of various extracted esterified bacteriochlorophylls. Methods and data are described in the publication (Wang et al., 2014). All .raw files are from a Thermo instrument and can be opened with Xcalibur software by Thermo.
Alternatively, files may be opened using publically available software: MZmineThis work was partly supported by funds from the NSF Plant Genome Research Program grant IOS-1238812Hegeman, Adrian Daniel; Freund, Dana M.; Tang, Joseph, K.. (2015). LC-MS/MS Data from Analysis of Bacteriochlorophylls. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/172269
Ms. Felesha Love, Spelman College, January 2016
No full textThis video is a conversation with Felesha Love. Ms. Love talks about her book, "Brave Leap to Freedom: Integrating Mind, Body, and Spirit to Cultivate Healthy Relationships". Jordan Moore, AUC Woodruff Library, is the interviewer
DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS-Based Untargeted Metabolomics
No full textSWATH-MS-based
data-independent acquisition mass spectrometry (DIA-MS)
technology has been recently developed for untargeted metabolomics
due to its capability to acquire all MS2 spectra with high quantitative
accuracy. However, software tools for deconvolving multiplexed MS/MS
spectra from SWATH-MS with high efficiency and high quality are still
lacking in untargeted metabolomics. Here, we developed a new software
tool, namely, DecoMetDIA, to deconvolve multiplexed MS/MS spectra
for metabolite identification and support the SWATH-based untargeted
metabolomics. In DecoMetDIA, multiple model peaks are selected to
model the coeluted and unresolved chromatographic peaks of fragment
ions in multiplexed spectra and decompose them into a linear combination
of the model peaks. DecoMetDIA enabled us to reconstruct the MS2 spectra
of metabolites from a variety of different biological samples with
high coverages. We also demonstrated that the deconvolved MS2 spectra
from DecoMetDIA were of high accuracy through comparison to the experimental
MS2 spectra from data-dependent acquisition (DDA). Finally, about
90% of deconvolved MS2 spectra in various biological samples were
successfully annotated using software tools such as MetDNA and Sirius.
The results demonstrated that the deconvolved MS2 spectra obtained
from DecoMetDIA were accurate and valid for metabolite identification
and structural elucidation. The comparison of DecoMetDIA to other
deconvolution software such as MS-DIAL demonstrated that it performs
very well for small polar metabolites. DecoMetDIA software is freely
available at https://github.com/ZhuMSLab/DecoMetDIA
DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS-Based Untargeted Metabolomics
No full textSWATH-MS-based
data-independent acquisition mass spectrometry (DIA-MS)
technology has been recently developed for untargeted metabolomics
due to its capability to acquire all MS2 spectra with high quantitative
accuracy. However, software tools for deconvolving multiplexed MS/MS
spectra from SWATH-MS with high efficiency and high quality are still
lacking in untargeted metabolomics. Here, we developed a new software
tool, namely, DecoMetDIA, to deconvolve multiplexed MS/MS spectra
for metabolite identification and support the SWATH-based untargeted
metabolomics. In DecoMetDIA, multiple model peaks are selected to
model the coeluted and unresolved chromatographic peaks of fragment
ions in multiplexed spectra and decompose them into a linear combination
of the model peaks. DecoMetDIA enabled us to reconstruct the MS2 spectra
of metabolites from a variety of different biological samples with
high coverages. We also demonstrated that the deconvolved MS2 spectra
from DecoMetDIA were of high accuracy through comparison to the experimental
MS2 spectra from data-dependent acquisition (DDA). Finally, about
90% of deconvolved MS2 spectra in various biological samples were
successfully annotated using software tools such as MetDNA and Sirius.
The results demonstrated that the deconvolved MS2 spectra obtained
from DecoMetDIA were accurate and valid for metabolite identification
and structural elucidation. The comparison of DecoMetDIA to other
deconvolution software such as MS-DIAL demonstrated that it performs
very well for small polar metabolites. DecoMetDIA software is freely
available at https://github.com/ZhuMSLab/DecoMetDIA
DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS-Based Untargeted Metabolomics
No full textSWATH-MS-based
data-independent acquisition mass spectrometry (DIA-MS)
technology has been recently developed for untargeted metabolomics
due to its capability to acquire all MS2 spectra with high quantitative
accuracy. However, software tools for deconvolving multiplexed MS/MS
spectra from SWATH-MS with high efficiency and high quality are still
lacking in untargeted metabolomics. Here, we developed a new software
tool, namely, DecoMetDIA, to deconvolve multiplexed MS/MS spectra
for metabolite identification and support the SWATH-based untargeted
metabolomics. In DecoMetDIA, multiple model peaks are selected to
model the coeluted and unresolved chromatographic peaks of fragment
ions in multiplexed spectra and decompose them into a linear combination
of the model peaks. DecoMetDIA enabled us to reconstruct the MS2 spectra
of metabolites from a variety of different biological samples with
high coverages. We also demonstrated that the deconvolved MS2 spectra
from DecoMetDIA were of high accuracy through comparison to the experimental
MS2 spectra from data-dependent acquisition (DDA). Finally, about
90% of deconvolved MS2 spectra in various biological samples were
successfully annotated using software tools such as MetDNA and Sirius.
The results demonstrated that the deconvolved MS2 spectra obtained
from DecoMetDIA were accurate and valid for metabolite identification
and structural elucidation. The comparison of DecoMetDIA to other
deconvolution software such as MS-DIAL demonstrated that it performs
very well for small polar metabolites. DecoMetDIA software is freely
available at https://github.com/ZhuMSLab/DecoMetDIA
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