Difference between revisions of "Team:IIT-Madras/Collaborations"

Latest revision as of 02:48, 31 October 2017

Team IIT-Madras

Collaborations

Team IISc-Bangalore: A Machine Learning Algorithm for Cell Counting

Team IISc worked towards developing a machine learning algorithm to count cells in a hemocytometer.
The objective of the collaboration was to provide the IISc Team with sufficient data on the growth curve characteristics of Saccharomyces cerevisiae to enable them to train their machine learning algorithm. Optical Density(OD) measurements to monitor the growth curve becomes unreliable due to the large sizes of yeast cells (which distorts the linear correlation between OD and biomass), it was necessary to measure the cell count of yeast cultures. Haemocytometry is the most common method used to monitor the growth rate and biomass of yeast cultures. This process is very time-consuming and involves tedious labour in counting cells for each measurement. Our team performed two growth curves each spanning 16 hours and the images were generated which were to be used by their algorithm to analyze. Using Haemocytometry, a manual cell count of the yeast cell samples at each timepoint was performed and this data along with their corresponding images were submitted. Read more at Team IISc-Bangalore's wiki

ChassiDex: Feedback and data contribution by Team INSA-UPS France

Team INSA-UPS_France has worked with 3 diverse organisms for their project and we are very grateful to them for filling up the data for Komagataella Pichia pastoris SMD1168H and Vibrio harveyi JMH626 in our database, ChassiDex. They also provided us feedback on the user experience. They said:
"Every important informations are required so I found it well-made. Our team would have definitely liked having this tool when we started this project."
Read their side of the story at Team INSA-UPS_France's wiki

ChassiDex: Data contribution by Team IISc-Bangalore

Team IISc-Bangalore generously conributed data for ChassiDex by filling up the data for Komagataella Pichia pastoris DSMZ 70382. We sincerely thank them for the entry.

ProtoCat for protocols! with Team Michigan_Software

ProtoCat(protocat.org) is a database for creating and sharing protocols. We have recommended their database under the protocols sections in the data entry/edit pages of our database.

All India iGEM meetup 2017 hosted by Team IISER Pune

An All India iGEM teams meetup was conducted by Team IISER-Pune-India and was attended by 9 teams from India. Team Peshawar from Pakistan also joined us video conferencing. The meetup was a valuable experience for us, as we exchanged ideas and gave critical feedback to each other, to help improve your projects and ideas. Read more at Team IISER-Pune-India's wiki

@@ Line 11: / Line 11: @@
              <h2>Team IISc-Bangalore: A Machine Learning Algorithm for Cell Counting</h2>
              Team IISc worked towards developing a machine learning algorithm to count cells in a hemocytometer.<br>
-             The objective of the collaboration was to provide the IISc Team with  sufficient data on the growth curve characteristics of <i>Saccharomyces cerevisiae</i> to enable them to train their machine learning algorithm. But since Optical Density(OD) measurements to monitor the growth curve becomes unreliable due to the large sizes of yeast cells (which distorts the linear correlation between OD and biomass), it was necessary to measure the cell count of yeast cultures. Haemocytometry is the most common method used to monitor the growth rate and biomass of yeast cultures. This process is very time-consuming and involves tedious labour in counting cells for each measurement. Our team performed two growth curves each spanning 16 hours and the images were generated which were to be used by their algorithm to analyze. Using Haemocytometry, a manual cell count of the yeast cell samples at each timepoint was performed and this data along with their corresponding images were submitted.
+             The objective of the collaboration was to provide the IISc Team with  sufficient data on the growth curve characteristics of <i>Saccharomyces cerevisiae</i> to enable them to train their machine learning algorithm. Optical Density(OD) measurements to monitor the growth curve becomes unreliable due to the large sizes of yeast cells (which distorts the linear correlation between OD and biomass), it was necessary to measure the cell count of yeast cultures. Haemocytometry is the most common method used to monitor the growth rate and biomass of yeast cultures. This process is very time-consuming and involves tedious labour in counting cells for each measurement. Our team performed two growth curves each spanning 16 hours and the images were generated which were to be used by their algorithm to analyze. Using Haemocytometry, a manual cell count of the yeast cell samples at each timepoint was performed and this data along with their corresponding images were submitted.
 Read more at <a href="https://2017.igem.org/Team:IISc-Bangalore/Collaborations#haemocytometry">Team IISc-Bangalore's wiki</a>
@@ Line 28: / Line 28: @@
 <br><br>
 <h2>ProtoCat for protocols! with Team Michigan_Software</h2>
-ProtoCat(protocat.org) is a database for creating and sharing protocols. We have recommended their database under the protocols sections in the data entry/edit pages of our database.
+ProtoCat(protocat.org) is a database for creating and sharing protocols. We have recommended their database under the protocols sections in the data entry/edit pages of our database.<br>
-<img src="https://static.igem.org/mediawiki/2017/e/ef/T--IIT-Madras--protocat.png">
+<img style="width: 100%;" src="https://static.igem.org/mediawiki/2017/e/ef/T--IIT-Madras--protocat.png">
+<br><br>
 <h2> All India iGEM meetup 2017 hosted by Team IISER Pune </h2>
+An All India iGEM teams meetup was conducted by Team IISER-Pune-India and was attended by 9 teams from India. Team Peshawar from Pakistan also joined us video conferencing. The meetup was a valuable experience for us, as we exchanged ideas and gave critical feedback to each other, to help improve your projects and ideas. Read more at <a href="https://2017.igem.org/Team:IISER-Pune-India/Collaborations"> Team IISER-Pune-India's wiki</a>
          </div>