19,290 Works

PeakXus: a comprehensive peak calling software for ChIP-Nexus and ChIP-exo

Tuomo Hartonen, Biswajyoti Sahu, Kashyap Dave, Teemu Kivioja & Jussi Taipale
Novel chromatin immunoprecipitation (ChIP) experiments ChIP-Nexus [1] and ChIP-exo [2] allow studying transcription factor (TF) binding with unprecedented accuracy. True TF binding locations are separated from noise by peak calling softwares.Most peak calling softwares search binding events by creating a model of "true" peaks from the sites with highest enrichment in the ChIP-experiments and then accepting only the peaks resembling this model. It is however known that most TFs bind cooperatively with other TFs, form...

Combining high throughput sequencing data to improve identification of transcription factor binding

Alex Essebier & Mikael Bodén
Identifying gene targets of transcription factors (TFs) is challenging due to the complex nature of TF binding. In particular, the ability of a TF to regulate genes over large distances. Combining high throughput sequencing datasets adds epigenetic detail to individual binding sites. Using this detail, as well as a binding site’s location, we can better distinguish a TF’s binding mode and set of gene targets. Here, we use Math1 in Cerebellar granule neuron precursors as...

Cutaneous microvascular responses to reactive hyperaemia and their relation to small arterial compliance in healthy males

Christopher Wright
Small (C2) arterial stiffness has been suggested to parallel endothelial reactivity and has led researchers to suggest parameters of arterial stiffness may be alternative measures to brachial sonographic assessments of flow-mediated dilatation (FMD). However, past studies comparing these measures can be criticized. In addition to %FMD responses, we recorded concurrent hyperaemic responses of the microcirculation to allow the comparison of C2 with %FMD as well as microvascular reactivity.

Raw data of disease severity indicators in lupus.

Abidullah Khan, Iqbal Haider, Maimoona Ayub & Salman Khan
This file contains data regarding disease severity indicators and demographics of patients with SLE. This coded data was stored on SPSS version 16. Group: 1, active-SLE; 2, inactive-SLE. Gender: 1, male; 2, female. SLEDAI, systemic lupus erythematosus disease activity index; MPV, mean platelet volume; ESR, erythrocyte sedimentation rate; WBC, white blood cell (thousand/mm3); Hb, hemoglobin (gm/dl); platelets, platelet count × 103.

Long k-mer clustering for scalable and accurate biological search

Timothy Chappell, Lawrence Buckingham, Shlomo Geva, Paul Greenfield, Wayne Kelly & Jim Hogan
BLAST, the Basic Local Alignment Search Tool, remains the dominant method for general purpose search and sequence comparison in molecular biology. While a number of alternatives – including some based directly on BLAST itself – are significantly faster, this efficiency may come at the cost of sensitivity, with performance degrading sharply for more divergent targets. In many cases, the underlying representation – through k-mer indices and similar approaches – proves highly effective at finding close...

Navigating the research data life cycle

Philippa Griffin, Rudi Appels, Dieter Bulach, Kevin Dudley, Gabriel Keeble-Gagnere, Andrew Pask, Bernard Pope, Ute Roessner, Torsten Seemann, Dan Bolser, Jyoti Khadake, Suzanna Lewis, Sandra Orchard, Sonika Tyagi, Andrew Lonie & Maria Victoria Schneider
Where does your research data go once you’ve published your paper? Can you do better? Good data management spans all stages of the data life cycle: finding, collecting, integrating, processing, visualising, analysing, publishing, sharing and reusing data and metadata. EMBL Australia Bioinformatics Resource (EMBL-ABR) aims to increase Australia’s capacity to deal with the large heterogeneous data sets now part of modern life science and biomedical research, in line with FAIR principles, so that data are...

Training efforts in the Netherlands: combining forces to provide data – related training for the life science research community

Celia Van Gelder, Sanne Abeln, Rita Azevedo, Luiz Olavo Bonino Da Silva Santos, Jeroen Engelberts, Rob Hooft, Mateusz Kuzak, Leon Mei, Marco Roos, Merlijn Van Rijswijk, Andrew Stubbs & Jaap Heringa
In this era of big data, new skills and competences are needed for life scientists, technologists and data experts. Many people with heterogeneous backgrounds have to be trained. By combining the education expertise present in the Netherlands we work towards establishing a comprehensive, internationally acclaimed and sustainable training and education course portfolio for Life Sciences Research & Technology with a focus on training in new technologies and data integration and stewardship. Our efforts cross bridges...

Predicting multicellular function through multi-layer tissue networks

Marinka Zitnik & Jure Leskovec
Understanding the functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Here we present OhmNet, a hierarchy-aware unsupervised node feature learning approach for multi-layer networks. We build a multi-layer network, where each layer represents molecular interactions in a different human tissue. OhmNet then automatically learns a mapping of proteins, represented as nodes, to a neural embedding...

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