Time to Shrink the National Institute of Health (NIH)?

In his recent budget, President Trump proposed to reduce taxes wasted in the NIH Money Pit sinkhole by twenty percent. Such a big cut will most likely not be approved by the Congress, because the political stars are aligning against it. The economic stars, on the other hand, are aligned in favor of drastic reduction of NIH funding in the coming years. We explained why in a post written four years ago. Shutting down parts of NIH, or even the entire agency, will not be an unmitigated disaster for science, and if at all, will be beneficial. We made an appeal to close NHGRI in “Let’s Discuss - Is it Time to Shut Down NHGRI?” and also wrote - “How Much Will the Americans Suffer, If NIH Shuts Down?”.

Is Google Tweaking Search Results to Block Our Posts Critical of NIH Director?

Every once in a while, we use Google search to find links to old posts in our blog. The method seemed to have worked without failure until today. Today we were looking for an earlier post critical of a paper by Francis Collins and Google never gave us the link, no matter how hard we searched for it. It is noteworthy that even after typing the entire title and adding ‘homolog.us’ on the search box, we do not find the relevant post anywhere in the first several pages of the Google results. Is some organization paying Google to block our posts critical of NIH? We present the evidence from four search engines (google, duckduckgo, bing, yahoo). You explain what is going on.

Gullible's Troubles

Apologies to the readers for not being able to make this week’s scheduled posts. Instead I am posting an entertaining essay on the birth of molecular biology. It is from a autobiographical book published in 1976. Any guessing the author will earn 99.99 homolog.us points :).

Another Tutorial - This Time on Pevzner's Videos

Grab them here on the left sidebar in bioinformatics courses section at the link ‘Pevzner Course’. I am still in the process of annotating the sets, including cross-linking similar sections.

A Tutorial with Ben Langmead's Bioinformatics Videos

Genome assembly algorithms through jigsaw puzzles - III

This is the third installment of “genome assembly algorithms through jigsaw puzzles”. We usually post them here every Tuesday, although we are late this week. You can find all those pieces in one place (and some more) at this link. We are developing this tutorial to explain genome assembly algorithms in a simple manner. In fact, rather than explaining, we expect you to discover the answer by manually solving a jigsaw puzzle. Later we show you how your solutions are related to the commonly used algorithms and their variations.

Tuesday Review - SAVE your day for CRISPR, Nature Fake News and Other Stories

1. SAVE your day for CRISPR

Two biorxiv papers cover the important topic of making CRISPR analysis user-friendly. In this context, we also included references to several other available CRISPR analysis tools for the benefit of our readers.

Genome assembly algorithms through jigsaw puzzles - II

This is the second installment of “genome assembly algorithms through jigsaw puzzles”. We post them here every Tuesday. You can find all those pieces in one place (and some more) at this link. We are developing this tutorial to explain genome assembly algorithms in a simple manner. In fact, rather than explaining, we expect you to discover the answer by manually solving a jigsaw puzzle. Later we show you how your solutions are related to the commonly used algorithms and their variations.

Monday review - Myers' dBG Paper, Pacbio's Multiplexing and Bioinformaticians' Foray into Escapism

1. Correcting Long Noisy Reads Using de Bruijn Graphs

Great news - the algorithmic concepts for short read assembly developed over the last decade need not be unlearned. In the two papers presented below, Myers, Pevzner and their colleagues use de Bruijn graphs for assembly and error correction of long noisy reads.

KMC tools tutorial - II

Yesterday we looked into the newly released ‘kmc tools’. Today we will work out another simple problem so that you feel familiar with it. We really love this powerful program, because, as the authors have shown, they could reproduce the results of many previously published bioinformatics papers with only a few commands.

A tutorial on KMC tools

The new version of kmc includes a number of really cool utilities. You need to run the executable ‘kmc_tools’ to access them. Let us demonstrate some uses.

Genome assembly algorithms through jigsaw puzzles

We are developing this tutorial to explain genome assembly algorithms in a simple manner. In fact, rather than explaining, we expect you to discover the answer by manually solving a jigsaw puzzle. Later we show you how your solutions are related to the commonly used algorithms and their variations.

Monday review - KMC3 and other seXY topics

1. KMC3 is out

KMC2 is the best kmer counting tool and is included in our Pandora’s Toolbox. Newly published KMC3 packs many improvements to make the program even better. Here are the updates -

Online Bioinformatics Contest from Stepik/Rosalind

Dear Readers, Happy New Year ! Here is a great way to bring some fun and challenges to your new year. We got a note from Nikolay Vyahhi, who helped build Rosalind and Stepik, that their organization is hosting a bioinformatics competition. The details are posted below -

Roche Dumps Pacbio

Yesterday, Pacbio received its Christmas present for 2016. Roche decided to abruptly terminate its three year-long alliance with the company. During this collaboration, Roche paid Pacbio to develop the Sequel instrument and reserved the exclusive right to sell it in the human clinical market.

Business analysis - Oxford Nanopore

Investor warning: The following post is for entertainment purpose only, and should not be considered as financial advice of any sort. Please consult your favorite government-certified investment adviser or central banker regarding decisions on investing your life savings.

GRASS for Rapid Reannotation of RNAseq Data

Many exciting papers/preprints on RNAseq came out over the last few months. Among them, a recently posted preprint solves an important problem - improving annotations based on new RNAseq data. There were other papers on quantification, compression and search, and we like to cover them in the next few posts.

Using Multidimensional Bloom filters to Search RNAseq Libraries - (i)

A number of recent papers are proposing to use multidimensional Bloom filters to identify genes from a large collection of RNAseq libraries. This post provides general perspective on these papers. In a later post, we will go in depth and explain the algorithm of the recent preprint by carrying out an example.

Postdoctoral Scholar Position in Comparative Plant Genomics and Bioinformatics

Job Title: Postdoctoral Scholar Position in Comparative Plant Genomics and Bioinformatics
The Computational Plant Genomics Lab invites applications for a Postdoctoral position in the Department of Ecology and Evolutionary Biology at the University of Connecticut. We focus on developing computational approaches that integrate next generation sequence data to address questions in non-model plants, particularly forest trees. The lab has the following ongoing projects: 1) Understanding the evolution of alternative translation initiation using RNA-seq data 2) Integrating new and existing approaches to gene prediction to improve the annotation of complex genomes 3) Analysis of gene family evolution and related comparative genomics questions 4) Detecting variation in populations from GBS and related sequence data.

Zipper plot for visualizing transcriptional activity of genomic regions

Abstract: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. The Zipper plot is an application that enables users to interrogate putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These features are obtained from publicly available datasets including CAGE-sequencing (CAGE-seq), ChIP-sequencing (ChIP-seq) for histone marks and DNase-sequencing (DNase-seq). The Zipper plot application requires three input fields (chromosome, genomic coordinate (hg19) of the TSS and strand) and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot.

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