BOL: Related items

DIY Transcriptomics

Abhi — Wed, 31 Jul 2024 01:19:26 -0500

A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source software using the R programming language and the Bioconductor suite of packages. This course follows a hybrid format in which online lectures are paired with in-person labs where students participate in hands-on, live coding exercises using real ‘omic datasets. The course is focused on datasets and topics central to infectious disease research, immunology, and One-Health, but the concepts and approaches covered are applicable to any genomic study.

https://diytranscriptomics.com

Address of the bookmark: https://diytranscriptomics.com

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

Bioinformatics postdoctoral position at inStem

Tue, 13 Feb 2018 03:18:54 -0600

One postdoctoral position is available in the area of Bioinformatics. This position is available through a highly collaborative project involving multiple labs.

The primary focus here would be to analyse and integrate high throughput data from various aspects of translation regulation including non-coding RNAs, mRNAs and modification of ribosomal RNA. We request the interested candidates to approach either

Dasaradhi Palakodeti (dasaradhip@instem.res.in)
Or
Ravi Muddashetty (ravism@instem.res.in)

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

Bioinformatics postdoctoral position at CSIR - Institute of Himalayan Bioresource Technology, Palampur (H.P.)

Thu, 05 Apr 2018 06:57:17 -0500

Walk-in-Interview is scheduled to be held on the date as mentioned below for selection of Suitable candidates in the following areas under the DBT sponsored projecT on purely temporary basis for the duration of the project(s) or till completion of projects whichever is earlier:

Project Title:
"Exploration of RBP-RNA interactions to reveal the post-transcriptional regulatory impact, and development of related tools and resource server".

Position: Research Associate (1 position)
Age : 35 years as on 02.05.2018
Salary : Rs.36,000/- P.M. + H.R.A.

as per the funds provisions in the respective projects.

Eligibility Criteria :
Essential Qualifications: Ph.D. in any area of Bioinformatics/ Computational Biology/ Life Sciences.
Desirable: Candidate having experience in Bioinformatics will be preferred.

Essential Qualifications: M.Tech. in Bioinformatics/ Computation Biology/ Computer Science or any related area with 3 years of research experience.

Selection Procedure : Walk In Interview

Date : 02 May, 2018
Time : 9:30 A.M.
Venue : CSIR-IHBT Palampur (H.P.)

For more info refer to following doc:

http://ihbt.res.in/components/com_chronoforms5/chronoforms/uploads/Recruitment/20180404125233_AdvtNo11_2018.pdf

Bioinformatics Project Assistant Level II position at CSIR - Institute of Himalayan Bioresource Technology, Palampur (H.P.)

Thu, 17 May 2018 01:53:17 -0500

Walk-in-Interview is scheduled to be held on the date as mentioned below for selection of Suitable candidates in the following areas under the DBT sponsored project on purely temporary basis for the duration of the project(s) or till completion of projects whichever is earlier:

Project Title:
"Exploration of RBP-RNA interactions to reveal the post-transcriptional regulatory impact, and development of related tools and resource server".

Position: Project Assistant Level II (1 position)
Age : 28 years as on 14.06.2018
Salary : Rs.25,000/- P.M.

as per the funds provisions in the respective projects.

Eligibility Criteria :
Essential Qualifications: M.Sc. in Bioinformatics / Computational Biology or any area of Bioinformatics with 55% marks.

Essential Qualifications: M.Sc. in any area of Life Sciences with 55% marks with Diploma in any area of Bloinformatics.

Essential Qualifications: B.Tech. / M.Tech. in Bioinformatics / Computer Science with 55% marks.

Selection Procedure : Walk In Interview

Date : 14 June, 2018
Time : 9:30 A.M.
Venue : CSIR-IHBT Palampur (H.P.)

For more info refer to following doc:

http://ihbt.res.in/components/com_chronoforms5/chronoforms/uploads/Recruitment/20180516114701_Advt15_2018.pdf

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

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

DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Jit — Sat, 25 Jan 2020 13:28:09 -0600

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant

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