Monthly Archives: November 2018

Vim and I

Vim is great. Despite its steep learning curve , it has many advantages and many loyal Vim followers will tell you that you should force yourself to use it.

Personally I started using Vim when I was ssh-ing into the group servers or into my computer in department. In such scenarios, I could not open the IDEs with the nice GUIs 🙁 However, as time passed, Vim started to grow on me. Now, I can list a few reasons why I think it is great, for example, it requires a small amount of memory to run, has a short start up time and can handle large files pretty well. 

Although, I am definitely not a Vim expert, I will tell you about some of the things I have added to my .vimrc. The .vimrc file is very handy for containing all your favourite settings, such as key mappings, custom commands, formatting and syntax highlighting. The file uses vimscript which is a programming language in itself. However, there is a lot of help online that tells you with what lines to add to your .vimrc. I would recommend installing Vundle which is a Vim plugin manager. 

Here I will list some cool things that I have discovered you can do with your .vimrc.   It has certainly made my life a bit nicer.

  1. Code Folding
    Most IDEs provide a way to collapse functions and classes that results in only seeing the function/class definition and hiding the code. To do this in Vim add the following lines to your .    vimrc 

    " Enable folding
set foldmethod=indent
set foldlevel=99
" Enable folding with the spacebar
nnoremap <space> za


    Alternatively, you can install the Vim plugin SimpylFold.

  2. Python indentation
    Vim does not do auto indention like many IDEs. To automatically do PEP-8 indentation for Python, add the following to your .vimrc . 

    " PEP indentation
au BufNewFile,BufRead *.py
\ set tabstop=4    
\ set softtabstop=4    
\ set shiftwidth=4    
\ set textwidth=79    
\ set expandtab    
\ set autoindent    
\ set fileformat=unix

    You can also install the Vim plugin vim-flake8 which is a static syntax and style checker for Python source code. It shows errors in a quickfix window and lets you jump to their location inside your code.

  3. Turn line numbers on 
    Rather than typing in  
    :set nu 
    every time you open your files. You can always have them turned on by adding :set nu to your .vimrc
  4. Autocompletion 
    When I switch from PyCharm to Vim I feel a bit lost without the autocompletion however, after a quick search I found many are using the Vim package Youcompleteme and it is awesome. 

Exciting new studies in OAS

Hi everyone!

Today is the day for another blog post from me. Here, I would like to give you an update on new studies, which were deposited in the Observed Antibody Space (OAS) resource and take a closer look at one of these studies. To date, we have curated 57 studies in OAS, where we provide raw nucleotide and numbered amino acid sequences for download. These amino acid sequences have been filtered using ANARCI parsing, which ensures that the sequences align to respective species HMM profiles and do not have unusual indels and frameshifts. More than 660 million numbered amino acid sequences are deposited in OAS, where every sequence keeps a link to its corresponding nucleotide sequence. Recently we added two more studies to OAS: Sheng et al., (2017) and Setliff et al., (2018). We numbered roughly 2.8 and 46 million sequences in Sheng et al., and Setliff et al., studies respectively. In this blog post, I would like to talk more about the uniqueness of Setliff et al., data.

Continue reading →

Finding the lowest energy conformation of given molecule!

Generating low-energy molecular conformers is important for many areas of computational chemistry, molecular modeling and cheminformatics. Many tools have been developed to generate conformers, including BALLOON (1), Confab (2), FROG2 (3),  MOE (4), OMEGA (5) and RDKit (6). The search algorithm implemented in these tools can be broadly classified as either systematic or stochastic. These algorithms primarily focus on generating geometrically diverse low-energy conformers. Here, we are interested in finding lowest energy conformation of a molecule instead of achieving geometric diversity and Bayesian optimization is used to find the lowest energy conformation (7). Continue reading →

Check My Blob

A brief overview and discussion of: Automatic recognition of ligands in electron density by machine learning .This paper aims to reduce the bias of crystallographers fitting ligands into electron density for protein ligand complexes. The authors train a supervised machine learning model using known ligand sites across the whole protein databank, to produce a classifier that can identify which common ligands could fit to that electron density.

Continue reading →