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Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc
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Started by laura, 05-09-2011, 04:42 AM
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35 responses
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by laura
12-05-2013, 02:37 AM
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Started by sci_guy, 01-23-2008, 11:19 PM
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236 responses
683,198 views
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by ECO
12-25-2009, 06:45 PM
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Started by ndovu9, 07-09-2013, 05:54 AM
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1 response
3,319 views
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by martinghunt
07-09-2013, 09:47 AM
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Started by scalefree, 07-01-2013, 11:44 PM
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4 responses
3,038 views
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by scalefree
07-09-2013, 09:08 AM
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Started by feralBiologist, 07-09-2013, 05:09 AM
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2 responses
2,205 views
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Started by akh22, 07-09-2013, 06:32 AM
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by akh22
07-09-2013, 06:32 AM
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Started by gene coder, 07-09-2013, 05:41 AM
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1,542 views
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by gene coder
07-09-2013, 05:41 AM
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Started by robelb4, 07-27-2011, 08:24 AM
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4 responses
3,633 views
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by metheuse
07-09-2013, 05:22 AM
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Started by gfmgfm, 07-08-2013, 09:54 PM
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2 responses
1,556 views
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by gfmgfm
07-09-2013, 02:11 AM
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Started by vivienne_lovely, 05-26-2013, 07:11 PM
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1 response
1,703 views
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Started by aggp11, 07-05-2013, 07:22 AM
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2 responses
4,571 views
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by shi
07-08-2013, 10:12 PM
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Started by dekkers, 07-08-2013, 07:16 PM
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0 responses
1,221 views
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by dekkers
07-08-2013, 07:16 PM
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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.
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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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Started by SEQadmin2, Today, 10:04 AM
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Today, 10:04 AM
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Started by SEQadmin2, Yesterday, 10:08 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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