Render Your Protein in Blender with Molecular Nodes

ASCP (Aspera Secure Copy Protocol) is a fast, reliable protocol for transferring large files, particularly over long distances or in conditions with network latency or packet loss. It uses a technology called fasp (Fast, Adaptive, and Secure Protocol) to maximize available bandwidth, making transfers faster than traditional methods like FTP.
For uploading data to NCBI, ASCP is particularly useful because it efficiently handles large datasets, such as genomic sequences or omics data. Its ability to resume interrupted transfers ensures that if a connection fails during an upload, the transfer continues from where it left off, saving time and bandwidth. ASCP also provides strong encryption, ensuring data security during the upload process.

The FoldX Suite builds on the strong fundament of advanced protein design features, already implemented in the successful FoldX3, and exploits the power of fragment libraries, by integrating in silico digested backbone protein fragments of different lengths. Such fragment-based strategy allows for new powerful capabilities: loop reconstruction, implemented in LoopX and peptide docking, implemented in PepX. The Suite also features an improved usability, thanks to a new boost Command Line Interface.

Nanopre and PacBio based Genome Assembly

Hi-C experiments explore the 3D structure of the genome, generating terabases of data to create high-resolution contact maps. Here, we introduce Juicer, an open-source tool for analyzing terabase-scale Hi-C datasets. Juicer allows users without a computational background to transform raw sequence data into normalized contact maps with one click. Juicer produces a hic file containing compressed contact matrices at many resolutions, facilitating visualization and analysis at multiple scales. Structural features, such as loops and domains, are automatically annotated.

NextDenovo is a string graph-based de novo assembler for long reads (CLR, HiFi and ONT). It uses a “correct-then-assemble” strategy similar to canu (no correction step for PacBio HiFi reads), but requires significantly less computing resources and storages. After assembly, the per-base accuracy is about 98-99.8%, to further improve single base accuracy, try NextPolish.

IgCaller is a python program designed to fully characterize the immunoglobulin gene rearrangements and oncogenic translocations in lymphoid neoplasms. It was originally developed to work with WGS data but it has been extended to work with WES and high-coverage, capture-based NGS data.

MUMmer is a system for rapidly aligning entire genomes. The current version (release 4.x) can find all 20 base pair maximal exact matches between two bacterial genomes of ~5 million base pairs each in 20 seconds, using 90 MB of memory, on a typical 1.8 GHz Linux desktop computer.

Whole Genome Sequencing (WGS) provides a deep insight into the DNA sequence of humans, animals, plants, and microbial genomes, with data analysis at the individual or population level. SNP/INDEL/CNV/SV and other variants of the genome can be fully analysed. Our sequencing analysis enables the identif wication of somatic and germline mutations as well as customized patterns of cancers and other diseases. (Novogene)

Learn about SeqKit, a powerful command-line toolkit designed for handling high-throughput sequencing data with ease and efficiency.

The cellranger vdj pipeline can be used to analyze sequencing data produced from Chromium Next GEM Single Cell 5' V(D)J libraries. It takes FASTQ files for V(D)J libraries and performs sequence assembly and paired clonotype calling. The pipeline uses the Chromium Cell Barcodes (also called 10x Barcodes) and UMIs to assemble V(D)J transcripts per cell. Clonotypes and CDR3 sequences are output as a .vloupe file which can be loaded into Loupe V(D)J Browser. Visit the What is Cell Ranger page to learn more about Cell Ranger for Immune Profiling. (10X Genomics)

A phylogenetic tree is a branching diagram that shows the evolutionary relationships among different species or entities, based on their physical or genetic characteristics. It illustrates how species have diverged from common ancestors over time. These trees are constructed using morphological or genetic data and are used in biology, epidemiology, and conservation to understand the evolutionary history and relationships of organisms.

The blog post delves into the realm of PacBio sequencing, elucidating its significance in the world of next-generation sequencing. Contrasting PacBio with other sequencing technologies, such as Illumina's short-read and Oxford Nanopore's long-read sequencing, the article highlights the unique advantages and challenges posed by each. The comprehensive PacBio data analysis pipeline is elucidated step by step, from raw data collection to final report generation. A special section is dedicated to comparing tools used in the PacBio pipeline, offering insights into their strengths and limitations.

Gene regulation plays a crucial role in various biological processes, and understanding its mechanisms is essential for advancing our knowledge in life sciences. The Advent of ATAC-seq, a powerful tool for mapping open chromatin regions, has revolutionized the study of gene regulation by providing insight into the regulatory elements that control gene expression. This review aims to provide an overview of the current state of ATAC-seq applications in various fields, including stem cell biology, cancer research, neurobiology, immunology, plant biology, microbiology, drug discovery, personalized medicine, and synthetic biology. We discuss the advantages and limitations of ATAC-seq and highlight its potential for identifying new therapeutic targets and developing personalized therapies. Overall, ATAC-seq has proven to be a valuable tool for unlocking gene regulation and has the potential to lead to significant breakthroughs in many areas of life science research.

Pseudotime analysis provides a transformative lens into cellular dynamics, offering an avenue to chart the developmental journey of individual cells. This primer introduces the novice to the realm of pseudotime and its significance in the intricate landscape of cell differentiation and gene expression. Utilizing Monocle, a pioneering tool in this domain, the article elucidates how cellular trajectories are constructed from single-cell RNA-sequencing data. The comparison of Monocle with its contemporaries highlights its robustness in handling complex trajectories and its unparalleled flexibility. As the biological world delves deeper into cellular intricacies, tools like Monocle stand as indispensable allies in unearthing the secrets of cellular progression. This article serves as a beacon for those navigating the vast ocean of single-cell analysis.