BOL: Related items

How to sequence the human genome - Mark J. Kiel

Fri, 30 May 2014 13:24:11 -0500

View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence. Lesson by Mark J. Kiel, animation by Marc Christoforidis.

Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data

Neel — Fri, 25 Feb 2022 04:42:09 -0600

This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.

Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:

Address of the bookmark: https://github.com/KamilSJaron/smudgeplot

Entire Human Genome Sequencing !

LEGE — Tue, 02 Apr 2024 01:19:29 -0500

Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.

Here are few companies:

https://mynucleus.com/

https://myome.com/

https://nebula.org/whole-genome-sequencing-dna-test/

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

Biological databases !

BioStar — Wed, 12 Feb 2020 01:16:29 -0600

Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...

ftp://ftp.ncbi.nih.gov/genomes/

https://hgdownload.soe.ucsc.edu/downloads.html

Address of the bookmark: ftp://ftp.ncbi.nih.gov/genomes/

Genome U-Plot: a whole genome visualization

Rahul Nayak — Fri, 13 Jul 2018 19:50:41 -0500

Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.

https://github.com/gaitat/GenomeUPlot

Address of the bookmark: https://github.com/gaitat/GenomeUPlot

The Human Genome Project Video 3D Animation Introduction Low)

Sat, 24 Aug 2013 19:01:19 -0500

Ra assembler - a de novo DNA assembler for third generation sequencing data

biogeek — Wed, 27 Dec 2017 20:36:54 -0600

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 development since 2014 in the form of several separate components that used to be run individually.
This project aims to ease the usage of Ra by integrating it into a complete de novo assembly tool.

Unlike other state-of-the-art assemblers, Ra does not have an error correction step. Instead, it relies on detecting overlaps using a very sensitive and specific overlapper ("graphmap -w owler", https://github.com/isovic/graphmap) and constructing and reducing an overlap graph (Ra layout, https://github.com/mariokostelac/ra).

Address of the bookmark: https://github.com/mariokostelac/ra-integrate/

HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures

Poonam Mahapatra — Thu, 04 Jun 2020 23:19:07 -0500

The HNADOCK server is to predict the binding complex structure between two nucleic acid molecules through a hierarchical docking algorihtm of an FFT-based global search strategy and an intrinsic scoring function for nucleic acid interactions. Users are required to provide the three-dimensional (3D) structures of the two molecules to be docked.

Address of the bookmark: http://huanglab.phys.hust.edu.cn/hnadock/

Basics of BLAST Programs !

BioStar — Fri, 26 Jul 2024 06:04:26 -0500

The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.

Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.