https://js.cgview.ca/ - CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.
CGView.js is the genome viewer of Proksee, an expert system for genome...
lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing...
NVIDIA and the Arc Institute have introduced Evo 2, a groundbreaking AI model designed to understand, predict, and generate DNA sequences. This marks a major advancement in computational biology, offering scientists an unprecedented tool to decode...
bioinf.shenwei.me - FASTA and FASTQ are basic and ubiquitous formats for storing nucleotide and protein sequences. Common manipulations of FASTA/Q file include converting, searching, filtering, deduplication, splitting, shuffling, and sampling. Existing tools only...
github.com - ProteoClade is a Python library for taxonomic-based annotation and quantification of bottom-up proteomics data. It is designed to be user-friendly, and has been optimized for speed and storage requirements.
ProteoClade helps you analyze two...
github.com - This pipeline performs the following steps:
Assembly of nanopore reads using Canu.
Polish canu contigs using racon (optional).
Map a paired-end Illumina dataset onto the contigs obtained in the previous steps...
github.com - dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs...
github.com - Integration of the Ra assembler - a de novo DNA assembler for third generation sequencing data developed on Faculty of Electrical Engineering and Computing (FER), Ruder Boskovic Institute (RBI) and Genome Institute of Singapore (GIS).
Ra is in...
atifrahman.github.io - SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.
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