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xieguigang · Feb 22, 2024 · b2bfb5d · b2bfb5d
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Showing 1 changed file with 46 additions and 19 deletions.
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@@ -651,7 +651,7 @@ <h2>Runtime &amp; System Requirements</h2>
                 </p>
 
                 <p>
-                    MZKit workbench supports Windows 10/11 64Bit system and Windows Server 2016/2019.
+                    MZKit workbench supports Windows 10/11 64Bit system and Windows Server 2016/2019/2022.
                 </p>
 
                 <p>
@@ -694,19 +694,33 @@ <h2 class="title text-center">License &amp; Copyright</h2>
                     analysis and data visualization. (2022) doi:<a
                         href="https://explore.openaire.eu/search/software?pid=10.5281%2Fzenodo.4603277">10.5281/zenodo.7040586</a>.
 
+                    <br />
+
+                <ul>
+                    <li>mzkit on ELIXIR biotools: <a href="https://bio.tools/mzkit">https://bio.tools/mzkit</a></li>
+                    <li>mzkit on SciCrunch: <a
+                            href="https://scicrunch.org/resources/data/record/nlx_144509-1/SCR_023936/resolver?q=SCR_023936&l=SCR_023936&i=rrid:scr_023936">RRID:SCR_023936</a>
+                    </li>
+                </ul>
+                <br />
                 <ul>
                     <li>
-                        MZKit® is a registered trademark of BioNovoGene Corporation, protected by copyright law and
+                        MZKit® is a registered trademark of BioNovoGene Corporation, protected by copyright law
+                        and
                         international treaties.
                     </li>
                     <li>
-                        RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All rights
+                        RawFileReader reading tool. Copyright © 2016 by Thermo Fisher Scientific, Inc. All
+                        rights
                         reserved.
                     </li>
                     <li>
-                        MS-DIAL was launched as a universal program for untargeted metabolomics that supports multiple
-                        instruments (GC/MS, GC/MS/MS, LC/MS, and LC/MS/MS) and MS vendors (Agilent, Bruker, LECO, Sciex,
-                        Shimadzu, Thermo, and Waters). Part of the spectrum algorithm in MZKit is developed based on the
+                        MS-DIAL was launched as a universal program for untargeted metabolomics that supports
+                        multiple
+                        instruments (GC/MS, GC/MS/MS, LC/MS, and LC/MS/MS) and MS vendors (Agilent, Bruker,
+                        LECO, Sciex,
+                        Shimadzu, Thermo, and Waters). Part of the spectrum algorithm in MZKit is developed
+                        based on the
                         <a href="http://prime.psc.riken.jp/compms/msdial/main.html">MS-DIAL project</a>.
                     </li>
                 </ul>
@@ -745,7 +759,8 @@ <h3 class="title">MIT License</h3>
                 <h3 class="title">Reference</h3>
 
                 <p>
-                    The development of the MZKit workbench library based on these works, you are also can cite these
+                    The development of the MZKit workbench library based on these works, you are also can cite
+                    these
                     works if you use MZkit software:
                 </p>
 
@@ -756,51 +771,63 @@ <h3 class="title">Reference</h3>
                         Metabolomics, Nature Communications, 2019, 10: 1516.
                     </li>
                     <li>
-                        Li S, Park Y, Duraisingham S, Strobel FH, Khan N, et al. (2013) Predicting Network Activity from
+                        Li S, Park Y, Duraisingham S, Strobel FH, Khan N, et al. (2013) Predicting Network
+                        Activity from
                         High Throughput Metabolomics. PLOS Computational Biology 9(7): e1003123.
                         https://doi.org/10.1371/journal.pcbi.1003123
                     </li>
                     <li>
-                        Pang, Z., Chong, J., Zhou, G., Morais D., Chang, L., Barrette, M., Gauthier, C., Jacques, PE.,
+                        Pang, Z., Chong, J., Zhou, G., Morais D., Chang, L., Barrette, M., Gauthier, C.,
+                        Jacques, PE.,
                         Li, S., and Xia, J. (2021) MetaboAnalyst 5.0: narrowing the gap between raw spectra and
                         functional insights Nucl. Acids Res. (doi: 10.1093/nar/gkab382)
                     </li>
                     <li>
-                        Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999). KEGG: Kyoto
+                        Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999). KEGG:
+                        Kyoto
                         Encyclopedia of Genes and Genomes. Nucleic acids research, 27(1), 29–34.
                         https://doi.org/10.1093/nar/27.1.29
                     </li>
                     <li>
-                        Tsugawa, H., Cajka, T., Kind, T., Ma, Y., Higgins, B., Ikeda, K., Kanazawa, M., VanderGheynst,
+                        Tsugawa, H., Cajka, T., Kind, T., Ma, Y., Higgins, B., Ikeda, K., Kanazawa, M.,
+                        VanderGheynst,
                         J., Fiehn, O., & Arita, M. (2015). MS-DIAL: data-independent MS/MS deconvolution for
                         comprehensive metabolome analysis. Nature methods, 12(6), 523–526.
                         https://doi.org/10.1038/nmeth.3393
                     </li>
                     <li>
-                        Sud M, Fahy E, Cotter D, Brown A, Dennis EA, Glass CK, Merrill AH Jr, Murphy RC, Raetz CR,
-                        Russell DW, Subramaniam S., LMSD: LIPID MAPS® structure database Nucleic Acids Research, 35: p.
+                        Sud M, Fahy E, Cotter D, Brown A, Dennis EA, Glass CK, Merrill AH Jr, Murphy RC, Raetz
+                        CR,
+                        Russell DW, Subramaniam S., LMSD: LIPID MAPS® structure database Nucleic Acids Research,
+                        35: p.
                         D527-32., DOI: 10.1093/nar/gkl838 , PMID: 17098933
                     </li>
                     <li>
-                        Fahy E, Sud M, Cotter D & Subramaniam S., LIPID MAPS® online tools for lipid research Nucleic
+                        Fahy E, Sud M, Cotter D & Subramaniam S., LIPID MAPS® online tools for lipid research
+                        Nucleic
                         Acids Research (2007), 35: p. W606-12., DOI: 10.1093/nar/gkm324 , PMID: 17584797
                     </li>
                     <li>
-                        Wishart DS, Guo AC, Oler E, et al., HMDB 5.0: the Human Metabolome Database for 2022. Nucleic
+                        Wishart DS, Guo AC, Oler E, et al., HMDB 5.0: the Human Metabolome Database for 2022.
+                        Nucleic
                         Acids Res. 2022. Jan 7;50(D1):D622–31. 34986597
                     </li>
                     <li>
-                        Mingxun Wang, Jeremy J. Carver, Vanessa V. Phelan, Laura M. Sanchez, Neha Garg, Yao Peng, Don
-                        Duy Nguyen et al. "Sharing and community curation of mass spectrometry data with Global Natural
+                        Mingxun Wang, Jeremy J. Carver, Vanessa V. Phelan, Laura M. Sanchez, Neha Garg, Yao
+                        Peng, Don
+                        Duy Nguyen et al. "Sharing and community curation of mass spectrometry data with Global
+                        Natural
                         Products Social Molecular Networking." Nature biotechnology 34, no. 8 (2016): 828. PMID:
                         27504778
                     </li>
 
-                    <li>Li, Y., Kind, T., Folz, J. et al. Spectral entropy outperforms MS/MS dot product similarity for
+                    <li>Li, Y., Kind, T., Folz, J. et al. Spectral entropy outperforms MS/MS dot product
+                        similarity for
                         small-molecule compound identification. Nat Methods 18, 1524–1531 (2021).
                         https://doi.org/10.1038/s41592-021-01331-z
                     </li>
-                    <li>Kind, T., Fiehn, O. Seven Golden Rules for heuristic filtering of molecular formulas obtained by
+                    <li>Kind, T., Fiehn, O. Seven Golden Rules for heuristic filtering of molecular formulas
+                        obtained by
                         accurate mass spectrometry. BMC Bioinformatics 8, 105 (2007).
                         https://doi.org/10.1186/1471-2105-8-105
                     </li>