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Techniques and protocol discussions on sample preparation, library generation, methods and ideas
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Started by vl80, 06-08-2014, 11:06 PM
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Started by Ayeh, 06-07-2014, 09:18 AM
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by Ayeh
06-07-2014, 09:18 AM
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Started by skerker, 06-05-2014, 05:56 PM
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1,675 views
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by skerker
06-05-2014, 05:56 PM
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Started by Darkside, 05-09-2014, 08:43 AM
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3 responses
2,117 views
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by lyndaben
06-05-2014, 01:46 PM
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Started by brynmcln, 06-03-2014, 07:56 PM
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3 responses
3,004 views
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by lorendarith
06-05-2014, 06:32 AM
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Started by TonyBrooks, 05-30-2014, 07:55 AM
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3 responses
2,140 views
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by TonyBrooks
06-02-2014, 02:37 AM
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Started by cordsp, 05-28-2014, 09:46 AM
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1,473 views
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by cordsp
05-28-2014, 09:46 AM
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Started by zwang0614, 05-28-2014, 12:33 AM
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3 responses
1,532 views
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Started by snarapor, 05-26-2014, 02:58 AM
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5 responses
5,688 views
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Started by Katerina Cvikova, 05-27-2014, 12:18 AM
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1 response
1,478 views
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by Etherella
05-27-2014, 01:02 AM
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Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
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Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...-
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Yesterday, 05:17 AM -
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by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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Yesterday, 10:08 AM
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07-07-2026, 11:05 AM
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