BOL: Related items

UCSC SARS-CoV-2 Genome Browser

Jit — Thu, 06 Jan 2022 06:48:40 -0600

The UCSC SARS-CoV-2 Genome Browser (https://genome.ucsc.edu/covid19.html) is an adaptation of our popular genome-browser visualization tool for this virus, containing many annotation tracks and new features, including conservation with similar viruses, immune epitopes, RT–PCR and sequencing primers and CRISPR guides. We invite all investigators to contribute to this resource to accelerate research and development activities globally.

Address of the bookmark: https://www.nature.com/articles/s41588-020-0700-8

MUM&Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (v4) to detect variants.

Rahul Nayak — Wed, 27 Apr 2022 04:34:12 -0500

MUM&Co is able to detect:
Deletions, insertions, tandem duplications and tandem contractions (>=50bp & <=150kb)
Inversions (>=1kb) and translocations (>=10kb)

Address of the bookmark: https://github.com/SAMtoBAM/MUMandCo

Genome Context Viewer (GCV)

LEGE — Sun, 21 May 2023 19:33:43 -0500

The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store operators can deploy federated instances of GCV, allowing users to compare genomes from different providers in a single interface.

Address of the bookmark: https://github.com/legumeinfo/gcv

Tools to access the quality of your assembled genome !

LEGE — Thu, 08 Aug 2024 23:31:18 -0500

FASTA VALIDATOR + SEQKIT RMDUP: FASTA validation
GENOMETOOLS GT GFF3VALIDATOR: GFF3 validation
ASSEMBLATHON STATS: Assembly statistics
GENOMETOOLS GT STAT: Annotation statistics
NCBI FCS ADAPTOR: Adaptor contamination pass/fail
NCBI FCS GX: Foreign organism contamination pass/fail
BUSCO: Gene-space completeness estimation
TIDK: Telomere repeat identification
LAI: Continuity of repetitive sequences
KRAKEN2: Taxonomy classification
HIC CONTACT MAP: Alignment and visualisation of HiC data
MUMMER → CIRCOS + DOTPLOT & MINIMAP2 → PLOTSR: Synteny analysis
MERQURY: K-mer completeness, consensus quality and phasing assessment

Early Genome Screening: The New Health Horoscope!

LEGE — Thu, 02 Jan 2025 19:44:36 -0600

In an era where precision medicine is reshaping healthcare, genome screening is emerging as the modern equivalent of a health horoscope. It offers insights into our biological "stars," unraveling predispositions to various conditions and empowering individuals with knowledge to navigate their health journeys proactively. But how reliable is this "horoscope," and how does it impact our lives?

Understanding Genome Screening

Genome screening involves analyzing an individual's DNA to identify genetic variations that may influence health and disease susceptibility. This can range from simple single-gene tests to comprehensive whole-genome sequencing. By peering into our genetic blueprint, we can uncover risks for conditions like cancer, diabetes, cardiovascular diseases, and even rare genetic disorders.

The process is straightforward: a saliva or blood sample is collected, and advanced sequencing technologies decipher the genetic code. The results provide a personalized health map, guiding lifestyle modifications, preventive measures, or medical interventions.

A Shift from Reactive to Proactive Healthcare

Traditional healthcare often focuses on treating diseases after they manifest. Genome screening flips this model on its head, enabling a shift toward prevention and early intervention. For instance:

Cancer Risk Management: Individuals with BRCA1 or BRCA2 gene mutations can opt for enhanced screening programs or preventive surgeries to mitigate their risk of breast and ovarian cancers.
Cardiovascular Health: Genetic predispositions to conditions like familial hypercholesterolemia can prompt early cholesterol monitoring and lifestyle adjustments.
Rare Diseases: Identifying carriers of genetic disorders can aid in family planning and reduce the incidence of inherited conditions.

The Ethical and Practical Concerns

While genome screening offers incredible promise, it is not without challenges:

Accuracy and Interpretation: Genetic predisposition does not guarantee disease. Misinterpretation of results can lead to unnecessary anxiety or unwarranted medical interventions.
Privacy and Data Security: Genetic data is highly sensitive. Ensuring robust data protection measures is crucial to prevent misuse.
Accessibility and Equity: High costs and limited availability may restrict access to genome screening, exacerbating health disparities.

Balancing Science and Pseudoscience

The comparison of genome screening to horoscopes isn’t entirely unfounded. Both offer predictive insights, but the scientific foundation of genome screening distinguishes it from astrology. Unlike the alignment of celestial bodies, genetic predictions are based on rigorous data and evidence. However, the probabilistic nature of genetic predispositions underscores the importance of interpreting results in conjunction with clinical and lifestyle factors.

The Road Ahead

As genome screening becomes more affordable and integrated into routine healthcare, its potential to transform lives is immense. Policymakers, healthcare providers, and genetic counselors must collaborate to ensure ethical implementation, public awareness, and equitable access.

Imagine a future where your genetic "horoscope" is a trusted guide, not just a prediction. Early genome screening could help chart a healthier path for generations, making it a cornerstone of personalized medicine. After all, our genes might just hold the key to unlocking a future of better health and well-being.

HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies

LEGE — Sat, 20 Sep 2025 09:34:04 -0500

HiTE is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.

panHiTE

We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

For detailed instructions, please refer to the panHiTE tutorial.

Address of the bookmark: https://github.com/CSU-KangHu/HiTE

Vvek's Lab

Thu, 26 Sep 2013 11:11:39 -0500

Broad Area of Research: RNA biology (microRNA, lncRNA), Stem cells, Functional genomics, Epigenomics and Cancer

RNAs, especially non-coding RNAs (such as microRNA, long ncRNAs) are recently identified to be very abundant in mammalian organisms and play some key roles in gene expression regulation, gene silencing, and also implicated in disease progression, stem cell pluripotency etc. Current research activities of our lab include analysis of expression pattern of ncRNAs by microarray and next-gen sequencing data and understanding the role of miRNAs or other regulatory RNAs in various diseases, especially cancer and validation by reporter assays (renilla/luciferase) and other experimental tools.

More @ http://vvekslab.in/index.html

Roderic Guigó Lab

Mon, 01 Sep 2014 17:13:00 -0500

Research in our group focuses on the investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, etc…). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences. Our group also actively participates in the analysis of many eukaryotic genomes and it in involved in the NIH-funded ENCODE project. Furthermore we are members of two large cancer-studies consortia (chronic lymphocytic leukemia "CLL" and Breast Cancer -Hospital del Mar/CRG/Roche-).

More at http://big.crg.cat/computational_biology_of_rna_processing

Hoffman Lab

Tue, 12 Jan 2016 02:47:41 -0600

They develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.

https://www.pmgenomics.ca/hoffmanlab/

The El-Sherif Group, Chair of Developmental Biology, Department of Biology - PhD Position

Sun, 19 Jan 2020 10:06:37 -0600

El-Sherif lab studies how genes are regulated to mediate patterning in Development. We use live and super-resolution imaging in addition to computational modeling to understand transcription dynamics at the single-cell level in three model systems: the fruit fly Drosophila melanogaster, the beetle Tribolium castaneum, and embryonic bodies derived from embryonic mouse stem cells.

In this project, you will use single-molecule techniques to label mRNA and DNA in (live and fixed) Drosophila embryos and fixed embryonic bodies. You will also use super-resolution microscopy to visualize protein condensates. Co-localization dynamics reflecting DNA-protein bindings and DNA looping events will be detected, analyzed, and used to test computational models of gene transcription.

Qualification:
MSc degree (or equivalent) in Biology, Biophysics, or Bioengineering

Experience in one or more of these areas: (1) molecular cloning, (2) imaging, (3) image analysis (using Matlab/Python/Java), (4) microfluidics, and (5) computational modeling.

How to Apply?
Send (1) your CV, (2) summary of research experience, and (3) email addresses of at least 2 references to ezzat.el-sherif@fau.de. Title your email ‘Transcription PhD Position’.

salary Grade.: E13
Total Time: 3 Jahre
Start: 01.01.2020.
End: 31.3.2020.

Address:
Dr. El-Sherif, Ezzat
Department Biologie
Professur für Zoologie (Entwicklungsbiologie) (Prof. Dr. Klingler)
Telefon 09131/85-28068, Fax 09131/85-28040, E-Mail: ezzat.el-sherif@fau.de