New answers tagged bioinformatics
The Next-Gen sequencers cannot sequence a very long stretch of DNA with good reliability (~150 for the recent model- HiSeq2000; even less for older models such as GA (40), GA-II (70), GA-IIx (90)). For increasing the confidence in a certain hit, it was sequenced from both the ends. For example, if you have selected 500bp DNA fragment, then after ligating ...
In Illumina sequencing, the DNA is (usually randomly) sheared into fragments. For paired end sequencing, fragments of a specific size range are selected and then sequenced from both sides. This results in two reads for each fragment. As read length is fixed, also the remaining "middle part" of the fragment is in a specific size range. In some cases there is ...
Colin the only way to go is Edgar's software write him firstname.lastname@example.org it's a thousand for a copy (in 2012) worth every penny.
My Vote goes to Mafft(insi) as it have ~86% accuracy and results in ~1.2 hour. Though fastest will be kalign takes only ~3 minutes to finish with an accuracy of 74.3%. For testing: For each of the 218 reference alignments in the benchmark, we applied eight alignment programs, resulting in a total of 1744 automatically constructed MSAs. The overall ...
It does sound like you have a lot of data. I would first try Robert Edgar's other newer tool UPARSE which is faster and can handle more data using the free 32-bit version. I think you'll mainly be limited by machine memory though, right? Did you try CD-Hit?
Okay, I finally figured it out. Basically there are those following 6 steps: Preparing a protein Preparing a ligand Generating a grid parameter file Generating maps and grid data files Generating a docking parameter file Running AutoDock Since the details are a little bit too lengthy for this post, I have written it up as a tutorial. A lot of people ...
You saw my last answer of your question? you can do that easily, just use prepare_ligand4.py -l my.mol2 -A "hydrogens"
You can use Autodock Vina. It provides an option to calculate local score only. displaying the individual contributions to the intermolecular score, before weighting (these are shown with "--score_only") Autodock is better tool in speed and accuracy than Autodock itself. For using it, you need : 1) Protein.pdbqt 2) Ligand.pdbqt 3) Config.txt (the ...
The e-value is required to have confidence in the hit, along with hit. Generally, an e-value of e-4 is preferred because, this cutoff is found to be sufficient enough by blast to confirm a hit as homolog. But, for a hit, an e-value greater than e-4 does not mean it is a homolog neither we can say it is not a homolog. We cannot surely infer anything from ...
Your problem will finally boil down to searching your sequence in the Blast databases. Performing Blast seems to be probably the best way to find out if your bacteria has that specific protein expressed or not. If you could not find it in the nearest species using Blast, then try running PSI-BLAST, which would return you distant homologs, by which you can ...
As the previous answer said, there are some public HP1 ChIP-seq data from D. melanogaster if not from the DGRP, from modENCODE and maybe others. In the case of modENCODE, they've published not only the reads, but also their peak calls (mapping with Eland + calling with MACS). BEDTools ( https://github.com/arq5x/bedtools2 )is a nice command line tool for ...
for biomart goto below link http://central.biomart.org/converter/#!/ID_converter/gene_ensembl_config_2 Also there is one more converter which i found pretty useful http://biodbnet.abcc.ncifcrf.gov/db/db2db.php#biodb
If you're working with BioCyc pathways you can use their REST-API for batch-downloading all genes for their pathways. You can run a wide range of queries including BioVelo-queries for all genes/compounds in a specified pathway, all pathways in organism etc. A query for all the pathways in B. subtilis would look like: ...
Have a look at these ChIP-seq data for HP1 in Drosophila: 1, 2 and 3. From ChIP-seq data you can find the distance between the TFBS peaks and the TSS of the gene. You can also look for nucleosome positioning and DNAse hypersensitvity regions; for the former, I am sure that data is available for Drosophila.
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