Rotate-and-Press: A Non-Visual Alternative to Point-and-Click

Most computer applications manifest visually rich and dense graphical user interfaces (GUIs) that are primarily tailored for an easy-and-efficient sighted interaction using a combination of two default input modalities, namely the keyboard and the mouse/touchpad. However, blind screen-reader users predominantly rely only on keyboard, and therefore struggle to interact with these applications, since it is both arduous and tedious to perform the visual \u27point-and-click\u27 tasks such as accessing the various application commands/features using just keyboard shortcuts supported by screen readers. In this paper, we investigate the suitability of a \u27rotate-and-press\u27 input modality as an effective non-visual substitute for the visual mouse to easily interact with computer applications, with specific focus on word processing applications serving as the representative case study. In this regard, we designed and developed bTunes, an add-on for Microsoft Word that customizes an off-the-shelf Dial input device such that it serves as a surrogate mouse for blind screen-reader users to quickly access various application commands and features using a set of simple rotate and press gestures supported by the Dial. Therefore, with bTunes, blind users too can now enjoy the benefits of two input modalities, as their sighted counterparts. A user study with 15 blind participants revealed that bTunes significantly reduced both the time and number of user actions for doing representative tasks in a word processing application, by as much as 65.1% and 36.09% respectively. The participants also stated that they did not face any issues switching between keyboard and Dial, and furthermore gave a high usability rating (84.66 avg. SUS score) for bTunes

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

Cuticular Compounds Bring New Insight in the Post-Glacial Recolonization of a Pyrenean Area: Deutonura deficiens Deharveng, 1979 Complex, a Case Study

Background: In most Arthropod groups, the study of systematics and evolution rely mostly on neutral characters, in this context cuticular compounds, as non-neutral characters, represent an underexplored but potentially informative type of characters at the infraspecific level as they have been routinely proven to be involved in sexual attraction. Methods and Findings: The collembolan species complex Deutonura deficiens was chosen as a model in order to test the utility of these characters for delineating four infraspecific entities of this group. Specimens were collected for three subspecies (D. d. deficiens, D. d. meridionalis, D. d. sylvatica) and two morphotypes (D. d. sylvatica morphoype A and B) of the complex; an additional species D. monticola was added. Cuticular compounds were extracted and separated by gas chromatography for each individual. Our results demonstrate that cuticular compounds succeeded in separating the different elements of this complex. Those data allowed also the reconstruction of the phylogenetic relationships among them. Conclusions: The discriminating power of cuticular compounds is directly related to their involvement in sexual attraction and mate recognition. These findings allowed a discussion on the potential involvement of intrinsic and paleoclimatic factors in the origin and the diversification of this complex in the Pyrenean zone. This character type brings the first advanc

Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (>40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r≥0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2

Identification of Networks of Co-Occurring, Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes

Fast index based algorithms and software for matching position specific scoring matrices

BACKGROUND: In biological sequence analysis, position specific scoring matrices (PSSMs) are widely used to represent sequence motifs in nucleotide as well as amino acid sequences. Searching with PSSMs in complete genomes or large sequence databases is a common, but computationally expensive task. RESULTS: We present a new non-heuristic algorithm, called ESAsearch, to efficiently find matches of PSSMs in large databases. Our approach preprocesses the search space, e.g., a complete genome or a set of protein sequences, and builds an enhanced suffix array that is stored on file. This allows the searching of a database with a PSSM in sublinear expected time. Since ESAsearch benefits from small alphabets, we present a variant operating on sequences recoded according to a reduced alphabet. We also address the problem of non-comparable PSSM-scores by developing a method which allows the efficient computation of a matrix similarity threshold for a PSSM, given an E-value or a p-value. Our method is based on dynamic programming and, in contrast to other methods, it employs lazy evaluation of the dynamic programming matrix. We evaluated algorithm ESAsearch with nucleotide PSSMs and with amino acid PSSMs. Compared to the best previous methods, ESAsearch shows speedups of a factor between 17 and 275 for nucleotide PSSMs, and speedups up to factor 1.8 for amino acid PSSMs. Comparisons with the most widely used programs even show speedups by a factor of at least 3.8. Alphabet reduction yields an additional speedup factor of 2 on amino acid sequences compared to results achieved with the 20 symbol standard alphabet. The lazy evaluation method is also much faster than previous methods, with speedups of a factor between 3 and 330. CONCLUSION: Our analysis of ESAsearch reveals sublinear runtime in the expected case, and linear runtime in the worst case for sequences not shorter than | [Formula: see text] |(m )+ m - 1, where m is the length of the PSSM and [Formula: see text] a finite alphabet. In practice, ESAsearch shows superior performance over the most widely used programs, especially for DNA sequences. The new algorithm for accurate on-the-fly calculations of thresholds has the potential to replace formerly used approximation approaches. Beyond the algorithmic contributions, we provide a robust, well documented, and easy to use software package, implementing the ideas and algorithms presented in this manuscript

Amplicon-Dependent CCNE1 Expression Is Critical for Clonogenic Survival after Cisplatin Treatment and Is Correlated with 20q11 Gain in Ovarian Cancer

Genomic amplification of 19q12 occurs in several cancer types including ovarian cancer where it is associated with primary treatment failure. We systematically attenuated expression of genes within the minimally defined 19q12 region in ovarian cell lines using short-interfering RNAs (siRNA) to identify driver oncogene(s) within the amplicon. Knockdown of CCNE1 resulted in G1/S phase arrest, reduced cell viability and apoptosis only in amplification-carrying cells. Although CCNE1 knockdown increased cisplatin resistance in short-term assays, clonogenic survival was inhibited after treatment. Gain of 20q11 was highly correlated with 19q12 amplification and spanned a 2.5 Mb region including TPX2, a centromeric protein required for mitotic spindle function. Expression of TPX2 was highly correlated with gene amplification and with CCNE1 expression in primary tumors. siRNA inhibition of TPX2 reduced cell viability but this effect was not amplicon-dependent. These findings demonstrate that CCNE1 is a key driver in the 19q12 amplicon required for survival and clonogenicity in cells with locus amplification. Co-amplification at 19q12 and 20q11 implies the presence of a cooperative mutational network. These observations have implications for the application of targeted therapies in CCNE1 dependent ovarian cancers

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

<p>Abstract</p> <p>Background</p> <p>Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer.</p> <p>Results</p> <p>To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage.</p> <p>Conclusions</p> <p>We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.</p

High-resolution genomic and expression analyses of copy number alterations in HER2-amplified breast cancer

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldINTRODUCTION: HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group, needed to be further characterized in large sample sets. METHODS: Genome-wide DNA copy number profiling, using bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH), and global gene expression profiling were performed on 200 and 87 HER2+ tumors, respectively. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number alterations (CNAs) in HER2+ tumors, which were related to a set of 554 non-HER2 amplified (HER2-) breast tumors. High-resolution oligonucleotide aCGH was used to delineate the 17q12-q21 region in high detail. RESULTS: The HER2-amplicon was narrowed to an 85.92 kbp region including the TCAP, PNMT, PERLD1, HER2, C17orf37 and GRB7 genes, and higher HER2 copy numbers indicated worse prognosis. In 31% of HER2+ tumors the amplicon extended to TOP2A, defining a subgroup of HER2+ breast cancer associated with estrogen receptor-positive status and with a trend of better survival than HER2+ breast cancers with deleted (18%) or neutral TOP2A (51%). HER2+ tumors were clearly distinguished from HER2- tumors by the presence of recurrent high-level amplifications and firestorm patterns on chromosome 17q. While there was no significant difference between HER2+ and HER2- tumors regarding the incidence of other recurrent high-level amplifications, differences in the co-amplification pattern were observed, as shown by the almost mutually exclusive occurrence of 8p12, 11q13 and 20q13 amplification in HER2+ tumors. GISTIC analysis identified 117 significant CNAs across all autosomes. Supervised analyses revealed: (1) significant CNAs separating HER2+ tumors stratified by clinical variables, and (2) CNAs separating HER2+ from HER2- tumors. CONCLUSIONS: We have performed a comprehensive survey of CNAs in HER2+ breast tumors, pinpointing significant genomic alterations including both known and potentially novel therapeutic targets. Our analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer