BOL: Related items

Genome in a Bottle (GIAB) Consortium

Jit — Sat, 25 Jan 2020 13:50:52 -0600

The Genome in a Bottle (GIAB) Consortium is a public-private-academic consortium hosted by NIST to develop the technical infrastructure (reference standards, reference methods, and reference data) to enable translation of whole human genome sequencing to clinical practice.

https://www.nist.gov/news-events/news/2016/09/nist-releases-new-family-standardized-genomes

Address of the bookmark: https://jimb.stanford.edu/giab/

AutoGluon: AutoML for Text, Image, and Tabular Data

Jit — Thu, 07 Jan 2021 05:33:17 -0600

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on text, image, and tabular data.

Address of the bookmark: https://github.com/awslabs/autogluon

NASA Open Science Data Repository

Abhi — Wed, 18 Dec 2024 11:54:47 -0600

The NASA Open Science Data Repository (OSDR) enables access to space-related data from experiments and missions that investigate biological and health responses of terrestrial life to spaceflight. The goal of OSDR is to enable multi-modal and multi-hierarchical fundamental space life science data be reused toward basic science, applied science, and operational outcomes for space exploration and knowledge discovery. These data include ‘omics, phenotypic, physiological, behavioral, hardware, environmental telemetry; raw, processed; tabular, text, code, bioimaging, and video.

https://www.nasa.gov/reference/osdr-data-processing/

Address of the bookmark: https://www.nasa.gov/osdr/

Bioinformatics tools to explore SSRs in genomes !

BioStar — Tue, 07 Mar 2023 13:06:15 -0600

There are several bioinformatics tools that can be used to explore Simple Sequence Repeats (SSRs), which are also known as microsatellites. Here are a few examples:

MISA: MISA (MIcroSAtellite) is a web-based tool that can identify SSRs in DNA sequences. It can be used to analyze nucleotide sequences from various organisms and can identify perfect, compound, and imperfect SSRs.
SSR Locator: SSR Locator is a web-based tool that identifies SSRs in both DNA and RNA sequences. It can identify perfect, compound, and imperfect SSRs, and can also filter out low complexity regions.
SciRoKo: SciRoKo is a software tool that can identify SSRs in DNA sequences. It can be used to analyze genomic and transcriptomic sequences from various organisms and can identify perfect, compound, and imperfect SSRs.
Primer3: Primer3 is a web-based tool that designs PCR primers for SSRs. It can design primers for perfect and imperfect SSRs, and can be used to design primers for SSRs in various organisms.
QDD: QDD (Quick Detection of Duplication) is a software tool that can identify SSRs in DNA sequences and can also identify duplicate loci. It can be used to analyze genomic and transcriptomic sequences from various organisms.

These are just a few examples of the many bioinformatics tools available for exploring SSRs. Depending on your specific needs and research questions, you may find that other tools are more appropriate for your analysis.

SALSA: A tool to scaffold long read assemblies with Hi-C

Jit — Fri, 15 Jun 2018 04:01:15 -0500

This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch. To use the latest version, first run the following commands: cd SALSA make To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2). If you consider using this tool, please cite our publication which describes the methods used for scaffolding. Ghurye, J., Pop, M., Koren, S., Bickhart, D., & Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).

Address of the bookmark: https://github.com/machinegun/SALSA

GraphPath: A graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network

LEGE — Wed, 27 Mar 2024 20:51:21 -0500

Achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels. In this paper, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling.

Address of the bookmark: https://github.com/amazingma/GraphPath