Using large-scale genomics data to identify driver mutations in lung cancer: methods and challenges

Lung cancer is the commonest cause of cancer death in the world and carries a poor prognosis for most patients. While precision targeting of mutated proteins has given some successes for never- and light-smoking patients, there are no proven targeted therapies for the majority of smokers with the disease. Despite sequencing hundreds of lung cancers, known driver mutations are lacking for a majority of tumors. Distinguishing driver mutations from inconsequential passenger mutations in a given lung tumor is extremely challenging due to the high mutational burden of smoking-related cancers. Here we discuss the methods employed to identify driver mutations from these large datasets. We examine different approaches based on bioinformatics, in silico structural modeling and biological dependency screens and discuss the limitations of these approaches

Luminescent properties of Bi-doped polycrystalline KAlCl4

We observed an intensive near-infrared luminescence in Bi-doped KAlCl4 polycrystalline material. Luminescence dependence on the excitation wavelength and temperature of the sample was studied. Our experimental results allow asserting that the luminescence peaked near 1 um belongs solely to Bi+ ion which isomorphically substitutes potassium in the crystal. It was also demonstrated that Bi+ luminescence features strongly depend on the local ion surroundings

Impact of Space Weather on Climate and Habitability of Terrestrial Type Exoplanets

The current progress in the detection of terrestrial type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favorable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of astrospheric, atmospheric and surface environments of exoplanets in habitable zones around G-K-M dwarfs including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles, and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favorable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro) physical, chemical, and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the habitable zone to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.Comment: 206 pages, 24 figures, 1 table; Review paper. International Journal of Astrobiology (2019

PuLSE:Quality control and quantification of peptide sequences explored by phage display libraries

The design of highly diverse phage display libraries is based on assumption that DNA bases are incorporated at similar rates within the randomized sequence. As library complexity increases and expected copy numbers of unique sequences decrease, the exploration of library space becomes sparser and the presence of truly random sequences becomes critical. We present the program PuLSE (Phage Library Sequence Evaluation) as a tool for assessing randomness and therefore diversity of phage display libraries. PuLSE runs on a collection of sequence reads in the fastq file format and generates tables profiling the library in terms of unique DNA sequence counts and positions, translated peptide sequences, and normalized 'expected' occurrences from base to residue codon frequencies. The output allows at-a-glance quantitative quality control of a phage library in terms of sequence coverage both at the DNA base and translated protein residue level, which has been missing from toolsets and literature. The open source program PuLSE is available in two formats, a C++ source code package for compilation and integration into existing bioinformatics pipelines and precompiled binaries for ease of use

An activity-based integrated land-use transport model for urban spatial distribution simulation

This research develops an activity-based integrated land use/transport interaction model based on the concepts – activities (mainly, households and employment activities), activity location and relocation for Chinese regions. It consists of a residential and employment location sub-model, a transport sub-model and an implicit real estate rent adjustment sub-model. The model is developed to model the urban activity distribution evolution, predict urban spatial development trends and examine various planning decision implications. It spatially distributes household and employment activity change of a study area by zone based on the current activity distribution, land use policies and the accessibilities of the zones. The model is subsequently calibrated to predict the distribution of households and employment activities in Beijing metropolitan area in 2025. Model results show that the resident and employment densities are still high in central Beijing in 2025, and most zones’ resident densities are higher than their employment densities. However, there is also significant population density increase along the 6th ring road, indicating the relocation trend of the residents and businesses to the outskirts. This is consistent with the government objectives to decentralize activities within the central urban area. The paper also suggests that the model should be used mainly in examining the possible differences arising from the adoption of different policies though predicting future of a city distribution proves feasible

Reduced growth and proliferation dynamics of nasal epithelial stem/progenitor cells in nasal polyps in vitro

10.1038/srep04619Scientific Reports4

Microbial ligand costimulation drives neutrophilic steroid-refractory asthma

Funding: The authors thank the Wellcome Trust (102705) and the Universities of Aberdeen and Cape Town for funding. This research was also supported, in part, by National Institutes of Health GM53522 and GM083016 to DLW. KF and BNL are funded by the Fonds Wetenschappelijk Onderzoek, BNL is the recipient of an European Research Commission consolidator grant and participates in the European Union FP7 programs EUBIOPRED and MedALL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities

The Anatomical Therapeutic Chemical (ATC) classification system, recommended by the World Health Organization, categories drugs into different classes according to their therapeutic and chemical characteristics. For a set of query compounds, how can we identify which ATC-class (or classes) they belong to? It is an important and challenging problem because the information thus obtained would be quite useful for drug development and utilization. By hybridizing the informations of chemical-chemical interactions and chemical-chemical similarities, a novel method was developed for such purpose. It was observed by the jackknife test on a benchmark dataset of 3,883 drug compounds that the overall success rate achieved by the prediction method was about 73% in identifying the drugs among the following 14 main ATC-classes: (1) alimentary tract and metabolism; (2) blood and blood forming organs; (3) cardiovascular system; (4) dermatologicals; (5) genitourinary system and sex hormones; (6) systemic hormonal preparations, excluding sex hormones and insulins; (7) anti-infectives for systemic use; (8) antineoplastic and immunomodulating agents; (9) musculoskeletal system; (10) nervous system; (11) antiparasitic products, insecticides and repellents; (12) respiratory system; (13) sensory organs; (14) various. Such a success rate is substantially higher than 7% by the random guess. It has not escaped our notice that the current method can be straightforwardly extended to identify the drugs for their 2nd-level, 3rd-level, 4th-level, and 5th-level ATC-classifications once the statistically significant benchmark data are available for these lower levels

Subfamily specific conservation profiles for proteins based on n-gram patterns

<p>Abstract</p> <p>Background</p> <p>A new algorithm has been developed for generating conservation profiles that reflect the evolutionary history of the subfamily associated with a query sequence. It is based on n-gram patterns (NP{<it>n,m</it>}) which are sets of <it>n </it>residues and <it>m </it>wildcards in windows of size <it>n+m</it>. The generation of conservation profiles is treated as a signal-to-noise problem where the signal is the count of n-gram patterns in target sequences that are similar to the query sequence and the noise is the count over all target sequences. The signal is differentiated from the noise by applying singular value decomposition to sets of target sequences rank ordered by similarity with respect to the query.</p> <p>Results</p> <p>The new algorithm was used to construct 4,248 profiles from 120 randomly selected Pfam-A families. These were compared to profiles generated from multiple alignments using the consensus approach. The two profiles were similar whenever the subfamily associated with the query sequence was well represented in the multiple alignment. It was possible to construct subfamily specific conservation profiles using the new algorithm for subfamilies with as few as five members. The speed of the new algorithm was comparable to the multiple alignment approach.</p> <p>Conclusion</p> <p>Subfamily specific conservation profiles can be generated by the new algorithm without aprioi knowledge of family relationships or domain architecture. This is useful when the subfamily contains multiple domains with different levels of representation in protein databases. It may also be applicable when the subfamily sample size is too small for the multiple alignment approach.</p