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Techniques and protocol discussions on sample preparation, library generation, methods and ideas
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Started by Tom Quinn, 11-16-2016, 01:43 PM
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3 responses
2,461 views
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by CoastGen
01-06-2017, 01:44 PM
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Started by ofar, 01-05-2017, 10:16 PM
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1 response
1,976 views
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by HESmith
01-06-2017, 04:58 AM
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Started by Fel, 12-22-2016, 06:25 PM
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1 response
2,082 views
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by pmiguel
01-03-2017, 12:25 PM
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Started by mjg, 12-22-2016, 09:40 AM
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2 responses
4,603 views
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by mjg
12-23-2016, 04:26 AM
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Started by dsher, 12-19-2016, 11:27 PM
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0 responses
2,908 views
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by dsher
12-19-2016, 11:27 PM
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Started by TimK, 12-12-2016, 06:58 PM
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0 responses
1,173 views
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by TimK
12-12-2016, 06:58 PM
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Started by oliPap, 12-09-2016, 06:46 AM
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6 responses
2,540 views
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by pmiguel
12-09-2016, 11:20 AM
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Started by StephanK, 12-09-2016, 05:00 AM
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0 responses
1,545 views
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by StephanK
12-09-2016, 05:00 AM
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Started by sjeschonek, 11-30-2016, 01:15 PM
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0 responses
2,790 views
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by sjeschonek
11-30-2016, 01:15 PM
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Started by jmp_0904, 11-28-2016, 03:52 PM
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2 responses
2,466 views
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Last Post
by luc
11-29-2016, 08:49 AM
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by SEQadmin2
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.
Probing...-
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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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07-01-2026, 11:43 AM -
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Yesterday, 10:08 AM
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Started by SEQadmin2, 07-07-2026, 11:05 AM
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07-07-2026, 11:05 AM
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