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4

You saw my last answer of your question? you can do that easily, just use prepare_ligand4.py -l my.mol2 -A "hydrogens"


1

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 ...


-2

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 ...


1

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 ...


0

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 ...


1

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


1

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: ...


1

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.


0

I've written a little script to remove identical sequences from fasta to get what I need. To print the list of removed sequences, uncomment line 22 #! /usr/bin/python3 # Removes identical sequences from fasta file import sys from Bio import SeqIO sequences={} #This is where sequences will be stored #likely calling str(seq.seq) on every test will be slower ...


0

I'm not sure if there's a way on GenBank, but UniProt offers UniRef where you can cluster redundant sequences or specify a lower cutoff (like 90% identity).


1

A couple of months ago I listened to a plant physiologist who strongly recommended recombination-based mapping over sequencing based mapping. The main reason he gave was the error-rate of 2nd generation sequencing. The error rate on Illumina platforms are about 1 % if I recall. In a small genome like that of Arabidopsis thaliana (157 Mbp) that accounts for ...


3

There is no perfect cut-off. It always depends on what you're doing. The e-value is basically a measure of how many such alignments you would expect to find in a database this size by chance. Therefore, e-values greater than 1 mean that you'd expect at least one alignment similar to what you've found by chance alone. As others have stated, the e-value is ...


3

The e-value is supposed to be a metric for the chance that an alignment could occur at random, but it is a crude estimate. As pointed out in other answers, this significantly does not include the length of the query sequence. It also does not include the conservation of the gene or the frequency of amino acids (in protein blasts). It does take into ...


2

E-value refers to the expected number of random hits for a given alignment score. Smaller it is more reliable is your match. There is no hard and fast rule for e-value cutoff. You can keep whatever you want depending on the level of stringency that you require. But you should note that for smaller sequences (< 30nt) there is always a higher likelihood of ...


2

http://ocw.mit.edu/courses/health-sciences-and-technology/hst-508-genomics-and-computational-biology-fall-2002/audio-lectures/ Download all the slides if you want good resources.


0

Ants, slime molds, and brains. Ants and slime molds use simple rules to generate pretty good transportation networks in an emergent way, and brains wire and rewire themselves constantly(adding/removing edges, but not usually nodes). Evolutionary networks, metabolic networks, and ecological networks are much harder to get concrete data sets from, because ...



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