Open Bioinformatics Foundation (OBF)

Mentors: Student: Anamika Yadav

Genstorian data refinement tool is pipeline to identify allele names in genotype of a model organism and strain information related to the allele from a table. The inventories of strain collections are typically kept as plain text in spreadsheets or similar tables. This is prone to errors and inconsistency because genotypes are input manually as plain text. The major challenge of the project is to migrate data from spreadsheets to the database. There is no standard set of rules followed to store allele information in a spreadsheet. Hence, the goal of the project is extract the information in spreadsheet then standardize it before storing it in a database.

Mentors: Student: Padmaja Bhol

The project aims at helping researchers find journals that require open source code easily. I aim to create a user interface that could seamlessly help users submit, edit and delete journals and a user-management system that could help with admin and user roles. React forms can replace the outdated google forms to sign manifestos by individuals or organizations, which comes with proper authentication and spam prevention. Apart from working on having maximum functionalities integrated, I shall be removing the frontend dependencies like React-Bootstrap to make the project more user-friendly. With that, CI pipelines shall be integrated through Github actions along with E2E tests written with Cypress.

Mentors: Student: Pranav Joshi

In this project, we need to implement a zero-cost abstraction using Modern C++, which can help us to switch between Structure of Arrays (SoA) and Array of Structures (AoS). This abstraction needs to be introduced at MSSpectrum and MSChromatogram levels. These are the 2 classes used in OpenMS, which currently uses vector<Peak1D> i.e. an Array of Structures.

Mentors: Student: Devesh Kumar

Currently, the backend of the journal policy tracker is on Flask and SQLite3. The goal for this project is to create a full-fledged functioning backend with Express, GraphQL, and MongoDB write extensive tests for that backend and then deploy it online. Switching to a no-SQL database for this use case will remove unneeded complexity from the database and make it more friendly to new contributors. Using GraphQL will eliminate a good amount of server load as the frontend will be able to precisely pick and choose the data that it wants to request. The main objectives of this project are: 1. Building a user Authentication API that will let people register and log in on the website as well as implementing the function of forgot-password. 2. Building Journal CRUD API which will allow our users to Create, Read, Update and Delete journal requests. 3. Writing proper documentation for all the implemented APIs. 4. Deploying this server online and making it fully functional.

Mentors: Student: Chalith Tharuka

Analyzing positional features/annotations in sequences is important in bioinformatics. Visualizing such data is quite a challenging task, considering the large amount of data to be displayed. The feature viewer is an open source javascript library developed to visualize biological data (referred to as features) mapped to a linear sequence (Paladin et al., 2020). For instance, it can be configured to visualize the location of protein domains or amino acid variations in a protein sequence. The feature viewer is being used in several popular bioinformatics resources such as neXtProt and COSMIC 3D. Currently, the feature viewer supports limited configurability options in the features displayed, such as the color, shape and on-click behavior. This is too restrictive for some of the possible use cases of the feature viewer, where more flexibility is required in the display of features. One such instance is when different types of amino acid variants should be displayed in a color-specific manner in the same feature track. The overall goal of this project is to improve the configurability of the feature viewer, such that it allows greater flexibility in the visualization of detailed biological data.