BOL: Related items

Metabuli 분리 improves metagenomic read classification

Abhi — Sat, 03 Jun 2023 20:15:04 -0500

Metabuli 분리 improves metagenomic read classification through metamers, DNA-AA k-mers, to be sensitive and specific, recovering 99% and 98% of DNA or AA classifiers.

Metabuli is metagenomic classifier that jointly analyze both DNA and amino acid (AA) sequences. DNA-based classifiers can make specific classifications, exploiting point mutations to distinguish close taxa. AA-based classifiers have higher sensitivity in detecting homology between query and reference sequences, leverageing higher conservation of AA sequences. Metabuli combines the information of both sequence types using a novel k-mer structure, metamer, to enable both specific and sensitive characterization of metagenomic samples. In addition, it can classify reads against a database of any size as long as it fits in the hard disk.

Address of the bookmark: https://github.com/steineggerlab/Metabuli

SVbyEye: R Package to visualize alignments between two or multiple DNA sequences

LEGE — Tue, 17 Sep 2024 02:34:57 -0500

R Package to visualize alignments between two or multiple DNA sequences including
a number of functionalities to facilitate processing of alignments in PAF format.

SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.

Author: David Porubsky

Address of the bookmark: https://github.com/daewoooo/SVbyEye

DNA RNA MEME

Neel — Thu, 28 Jan 2021 11:23:14 -0600

Explain the DNA and RNA with picture ...

eQuant : energy-based quality assessment of protein

Shruti Paniwala — Sat, 24 Jun 2017 19:24:24 -0500

Protein structures are of varying quality. Especially, in-silico modeled structures are prone to contain serious errors, which limit the usefulness and reliability of these particular protein structures.

eQuant is a service for structure quality assessment of single proteins, which utilizes a coarse-grained energy model. The overall quality is calculated as well as the reliability of individual residues. You can submit single PDB files or archives containing a set of proteins.

https://biosciences.hs-mittweida.de/equant/

Address of the bookmark: https://biosciences.hs-mittweida.de/equant/

FRODOCK 2.0: fast protein–protein docking server

Neel — Wed, 17 Oct 2018 04:31:30 -0500

frodock: a user-friendly protein–protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein–protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein–protein binding conformations that can be further refined with more computationally demanding strategies.

Address of the bookmark: http://frodock.chaconlab.org/

Caretta – A multiple protein structure alignment and feature extraction suite

Rahul Nayak — Fri, 18 Dec 2020 02:09:44 -0600

Caretta – a multiple protein structure alignment and feature extraction suite

Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.

Address of the bookmark: http://www.bioinformatics.nl/caretta/

Anders Krogh Lab

Mon, 30 Sep 2013 19:07:40 -0500

In a lot of my work in bioinformatics, I have been using hidden Markov models (HMMs). As a postdoc with David Haussler at UCSC we developed the so-called profile HMMs (refs). Since then I have applied HMMs to membrane proteins (refs) and gene identification (refs) and have worked on methods for such things as discriminative estimation of HMMs (refs) and alternative decoding algorithms etc. (refs).

Now my main interests are in gene regulation, where we work on promoter analysis; non-coding RNA, where miRNAs and structure prediction are the main areas; and protein structure, where the group is working on methods for structure prediction from sequence. To read more about these topics, please see the research pages.

Lab page @ http://wiki.binf.ku.dk/User:Krogh

GABi

Fri, 06 Dec 2013 16:43:01 -0600

GABi Research
The major researching fields defined as the GABi scope are described next:
Sequence Analysis
Protein Structure Prediction
Comparative Genomics
Functional Analysis of Residues on Protein Families
Gene/Protein Networks
Genome structure & base composition
Highthroughput data analysis from NGS

Lab Page http://gabi.cidbio.org/index/

Scientists map 17,294 proteins produced in human body

Jit — Thu, 29 May 2014 01:57:55 -0500

Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.

The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.

The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".

The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.

Reference:

http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html

http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme

http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.

https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB

Amino Acid Flash Tutorial

Jit — Mon, 11 Aug 2014 08:58:17 -0500

Protein is a part of every cell in your body, and no other nutrient plays as many different roles in keeping you alive and healthy. Protein is the building block of our body, and amino acids are the main areas of interest. We have emphasized on all 20 amino acids in this documentary movie. This documentary has been developed that emphasize on chemical structure, chemical formula, IUPAC name and other detail information of all 20 amino acids with the voice, picture with interactive button. This will be helpful for the entire biology and bioinformatics student.

How to run?

You need to install flash player or open it with web browser ( I guess you have installed flash plugin) to play.

Comment below if you like it. Thanks