BOL: Related items

Pango Lineage Analysis !

Abhi — Mon, 15 Nov 2021 03:38:29 -0600

The Pango nomenclature is being used by researchers and public health agencies worldwide to track the transmission and spread of SARS-CoV-2, including variants of concern. This website documents all current Pango lineages and their spread, as well as various software tools which can be used by researchers to perform analyses on SARS-COV-2 sequence data.

Address of the bookmark: https://cov-lineages.org/resources/pangolin/output.html

Applied Statistics for Bioinformatics using R

Neel — Thu, 30 Aug 2018 03:45:39 -0500

The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be introductory in explaining and programming elementary statistical concepts, thereby bridging the gap between high school levels and the specialized statistical literature

SeqCAT: Sequence Conversion and Analysis Toolbox

Neel — Fri, 14 Jun 2024 14:36:53 -0500

Your all-in-one solution for smooth conversion of sequence coordinates.

Designed for bioinformatics data analysis and daily laboratory work, SeqCAT simplifies sequence coordinate conversion. Extract gene and transcript information, manipulate sequences, and easily validate complex genetic events such as fusions with SeqCAT.

More at https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae422/7683049?login=false

Address of the bookmark: https://mtb.bioinf.med.uni-goettingen.de/SeqCAT/home

BETSY: A new backward-chaining expert system for automated development of pipelines in Bioinformatics

Jit — Mon, 17 Dec 2018 18:46:51 -0600

The BETSY provides a command-line interface and available at https://github.com/jefftc/changlab. A user first searches in the knowledge base for desired output and then BETSY develops an initial workflow to produce that data which is later examined by the user. The user can optimize the parameters, the algorithm to preprocess the data, and normalize it depending on the task.

Currently, BETSY consists of modules required for the microarray and next-generation sequencing data [4] such as expression analysis, classification, peak calling, and visualization.

Address of the bookmark: https://github.com/jefftc/changlab

PeGAS: A Comprehensive Bioinformatic Solution for Pathogenic Bacterial Genomic Analysis

LEGE — Mon, 01 Sep 2025 01:18:10 -0500

This is PeGAS, a powerful bioinformatic tool designed for the seamless quality control, assembly, and annotation of Illumina paired-end reads specific to pathogenic bacteria. This tool integrates state-of-the-art open-source software to provide a streamlined and efficient workflow, ensuring accurate insights into the genomic makeup of pathogenic microbial strains.

Address of the bookmark: https://github.com/liviurotiul/PeGAS

Tenure Track position in Bioinformatics at Institute of Neurobiology, UNAM, Querétaro, México

Mon, 10 Jun 2019 00:48:54 -0500

The Institute of Neurobiology UNAM (www.inb.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to develop an original research program in Bioinformatics with applications to neuroscience and to establish multidisciplinary collaboration with other members of the Institute. Applicants are expected to have a doctorate degree, postdoctoral experience related to bioinformatics or genome biology, and a strong track record of peer-reviewed publications. No previous experience in neuroscience is required.

Interested applicants must submit CV and addresses of three references to ataulfo@unam.mx.

Tenure Track position in Genomic Sciences

Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México

The International Laboratory for Human Genome Research, LIIGH-UNAM (www.liigh.unam.mx) offers a tenure-track position at the level of Assistant Professor (Investigador Asociado C) to perform research, teaching and formation of human resources in the area of: “Genomics of Mendelian Diseases”

Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page project to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019 ………………………………………………………………

Tenure Track position in Genomic Sciences

Laboratorio Internacional de Investigación sobre el Genoma Humano, UNAM Juriquilla, Querétaro, México

Applicants are expected to have a doctorate degree, postdoctoral experience related to the above mentioned area and a strong track record of peer-reviewed publications. Interested applicants must submit CV, email addresses of three references, and a three-page statement of research interests to Dr. Rafael Palacios, Coordinator of LIIGH-UNAM (palacios@liigh.unam.mx) before June 21, 2019

Single Cell RNAseq data analysis tutorial !!

Robert M Willioms — Mon, 27 Nov 2017 16:24:29 -0600

A major breakthrough (replaced microarrays) in the late 00’s and has been widely used since
Measures the average expression level for each gene across a large population of input cells
Useful for comparative transcriptomics, e.g. samples of the same tissue from different species
Useful for quantifying expression signatures from ensembles, e.g. in disease studies
Insufficient for studying heterogeneous systems, e.g. early development studies, complex tissues (brain)
Does not provide insights into the stochastic nature of gene expression

Following are the useful links:

Single Cell RNAseq data analysis Tutorial

A step-by-step workflow for low-level analysis of single-cell RNA-seq data

A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

SCell: single-cell RNA-seq analysis software

https://github.com/diazlab/SCell

Beta-Poisson model for single-cell RNA-seq data analyses

https://github.com/nghiavtr/BPSC

Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis

https://research.cchmc.org/pbge/sincera.html

SC3 – consensus clustering of single-cell RNA-Seq data

http://biorxiv.org/content/early/2016/09/02/036558

Citrus: A toolkit for single cell sequencing analysis

http://biorxiv.org/content/early/2016/09/14/045070

Single-Cell Resolution of Temporal Gene Expression during Heart Development

http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7

Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects

http://biorxiv.org/content/early/2016/11/15/087775

Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes

http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract

SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

http://biorxiv.org/content/early/2016/11/21/088856

SCOUP is a probabilistic model to analyze single-cell expression data during differentiation

https://github.com/hmatsu1226/SCOUP

scLVM is a modelling framework for single-cell RNA-seq data

https://github.com/PMBio/scLVM

Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories

https://github.com/jw156605/SLICER

SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality

http://www.morgridge.net/SinQC.html

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

https://github.com/zji90/TSCAN

Visualization and cellular hierarchy inference of single-cell data using SPADE

http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html

OEFinder: Identify ordering effect genes in single cell RNA-seq data

https://github.com/lengning/OEFinder

Industrial Training in Computer Aided Drug Designing (CADD)

RASA Life Sciences — Wed, 13 Nov 2019 05:00:44 -0600

Learn More about Computer Aided Drug Designing (CADD)!!!

#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,

Batch Starts From 18^th November 2019

#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will learn from industry leaders how to apply these skills in life science & have a command over software developing process by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/

Delta: a new Web-based 3D genome visualization and analysis platform

Jit — Wed, 20 Dec 2017 08:49:55 -0600

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Deltafeatures a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.

https://github.com/zhangzhwlab/delta

Address of the bookmark: https://github.com/zhangzhwlab/delta

Post Doc Computational Biology, Bioinformatics - Network Biology & Data Science, NGS (m/f/d)

Sat, 15 Feb 2020 06:13:35 -0600

https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential