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

Revision as of 15:09, 30 October 2017

Team IIT-Madras

Collaborations

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. 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. Read more at Team IISc-Bangalore's wiki

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              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.
+Read more at <a href="https://2017.igem.org/Team:IISc-Bangalore/Collaborations#haemocytometry">Team IISc-Bangalore's wiki</a>
+<br><br>
+<h2>iGEM India: Mini
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