BOL: Related items

List of useful machine / ai learning resources !

Rahul Nayak — Tue, 30 Mar 2021 08:56:06 -0500

ML cheatsheet !

https://github.com/remicnrd/ml_cheatsheet

Visual AI / ML

https://setosa.io/ev/

Simple and efficient tools for predictive data analysis

https://scikit-learn.org/stable/

Machine learning in Perl

Jit — Sun, 16 Feb 2020 15:32:03 -0600

this is a fourth blog post in the Machine learning in Perl series, focusing on the AI::MXNet, a Perl interface to Apache MXNet, a modern and powerful machine learning library.

If you're interested in refreshing your memory or just new to the series, please check previous entries over here: 1 2 3

https://metacpan.org/pod/AI::MXNet

Address of the bookmark: http://blogs.perl.org/users/sergey_kolychev/2018/07/machine-learning-in-perl-kyuubi-goes-to-a-modelzoo-during-the-starry-night.html

Bioinfo Lab

Fri, 04 Mar 2022 00:17:00 -0600

The Institute of Bioinformatics conducts internationally renowned research and provides profound education in bioinformatics. Its research focuses on development and application of machine learning and statistical methods in biology and medicine.

Contact:
Computer Science Building (Science Park 3)
Altenberger Str. 69, A-4040 Linz, Austria
Tel. +43 732 2468 4520 / Fax +43 732 2468 4539
E-mail secretary@bioinf.jku.at

http://www.bioinf.jku.at/

Project Associate-I | Project Associate-II | Senior Project Associate @ IGIB

Thu, 05 Aug 2021 16:11:32 -0500

Experience in Next Generation Sequencing (NGS) application and interest in Genomics/ Clinical / Translational Applications. OR Good computational programming skills and deep interest in working on interface of Genomics and Clinical application.

Project Scientist-I
Experimental / Computation analysis experience in highthroughput genomics/ clinical application.

Project Manager
Experience in handling large biological projects involving high-throughput genomics/ clinical application.

Scientific Administrative Assistant
Lab Work.

More at https://vinodscaria.genomes.in/positionsopen

New Machine Learning Packages in R

Rahul Nayak — Fri, 27 Mar 2020 12:11:21 -0500

Machine Learning

autokeras v1.0.1: Implements an interface to AutoKeras, an open source software library for automated machine learning. See README for an example.

MTPS v0.1.9: Implements functions to predict simultaneous multiple outcomes based on revised stacking algorithms as described in Xing et al. (2019). See the vignette to get started.

quanteda.textmodels v0.9.1: Implements methods for scaling models and classifiers based on sparse matrix objects representing textual data. It includes implementations of the Laver et al. (2003) wordscores model, the Perry & Benoit’s (2017) class affinity scaling model, and the Slapin & Proksch (2008) wordfish model. See the vignette to get started.

SeqDetect v1.0.7: Implements the automaton model found in Krleža, Vrdoljak & Brčić (2019) to detect and process sequences. See the vignette for examples and theory.

studyStrap v1.0.0: Implements multi-Study Learning algorithms such as Merging, Study-Specific Ensembling (Trained-on-Observed-Studies Ensemble), the Study Strap, and the Covariate-Matched Study Strap. and offers over 20 similarity measures. See Kishida, et al. (2019) for background and the vignette for how to use the package.

Machine learning training and courses in bioinformatics !

Rahul Nayak — Tue, 31 Dec 2019 19:33:07 -0600

Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.

More at http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/

Detect the sequence pattern and its location in fasta file with match and mismatches information.

Jit — Thu, 26 Sep 2013 15:02:53 -0500

This script is one of my old script to detect some centromeric pattern in chromosomes. User can also control the number of mismatches allowed through command line ..

To run:

perl centro.pl

Fiona Brinkman Laboratory

Sun, 14 Jul 2013 12:46:31 -0500

Infectious disease control needs to be made more “sustainable”. We need to reduce selective pressure on pathogens to evolve antibiotic resistance. We need to control infectious disease outbreaks and associated immune disorders with a better understanding of the genetic, environmental and social factors that impact disease spread and severity.

Research Area

Investigating the role in disease of both the microbe and its host (i.e immune system failure), using genomics and systems biology-based approaches
Using genomics and network analysis to characterize disease outbreaks and their environmental/social/genetic causes, and
Identifying new anti-infective and immune modulating therapies/biomarkers.

Link @ http://www.brinkman.mbb.sfu.ca/

BioProgramming

Jitendra Narayan — Sun, 14 Jul 2013 16:29:53 -0500

The completion of the first human genome drafts was just a start of the modern DNA sequencing era which resulted in further invention, improved development toward new advanced strategies of high-throughput DNA sequencing, so called the “high-throughput next generation sequencing” (HT-NGS). The decreasing genome sequencing cost and desire to explore and understand biological machanism at genomic level, speed up the genomic sequencing projects. In the fast growing HT-NGS technologies, the main challenge is to cope with the analysis of vast production of sequencing database through advanced bioinformatics tools. In oder to develope sotware/tools bioinformatician/ biological programmers need to expertise in any one one the programming language. However, sometime one language are not enough to handle all sort of biological needs, which compel us to learn new biologically suitable language to handle ever growing genome or protein sequences.

The next step after reading genetic code is writing a script to analyse and explore the hidden information. This tutorial is aimed to introduce you new biological programming languages with their packages/libraries, and assist in your scripting work.

Navigate the sub-section of this page [ see right hand side of the page for it ]

Livestock Functional Genomics Summer School (LFG 2013)

Fri, 02 Aug 2013 09:57:37 -0500

*Livestock Functional Genomics Summer School - Call for applications*

1st Livestock Functional Genomics Summer School (LFG 2013).

This School was designed for graduate students and early-stage researchers with interest in livestock genomics, who are engaged in projects that require knowledge in the field of computational biology.

Sixty selected participants will spend 13 days receiving theoretical and practical training in genomic data handling from internationally renowned experts.

After the course, the participant should understand the basis and the context of livestock big molecular data, and be able to manipulate high density genotypes, whole genome sequences and transcriptome data.

The Summer School will be held in Araçatuba-SP Brazil, from the 13th to the 21st of September 2013.

All accepted participants will have *expenses fully covered (air ticket, hotel and meals)*, including a free pass to the 5th International Symposium on Animal Functional Genomics http://www.isafg2013.org.br

Applicants will be selected based on their résumés. Application date is due by August 10th. Results will be announced in August 12th.

Please consult website: http://www.sciencesatellite.org.br/sschool