PathGAN: visual scanpath prediction with generative adversarial networks

“This is a post-peer-review, pre-copyedit version of an article published in: Computer Vision – ECCV 2018 Workshops. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-11021-5_25”.We introduce PathGAN, a deep neural network for visual scanpath prediction trained on adversarial examples. A visual scanpath is defined as the sequence of fixation points over an image defined by a human observer with its gaze. PathGAN is composed of two parts, the generator and the discriminator. Both parts extract features from images using off-the-shelf networks, and train recurrent layers to generate or discriminate scanpaths accordingly. In scanpath prediction, the stochastic nature of the data makes it very difficult to generate realistic predictions using supervised learning strategies, but we adopt adversarial training as a suitable alternative. Our experiments prove how PathGAN improves the state of the art of visual scanpath prediction on the iSUN and Salient360! datasets.Peer ReviewedPostprint (author's final draft

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

Genetic Analysis of Completely Sequenced Disease-Associated MHC Haplotypes Identifies Shuffling of Segments in Recent Human History

The major histocompatibility complex (MHC) is recognised as one of the most important genetic regions in relation to common human disease. Advancement in identification of MHC genes that confer susceptibility to disease requires greater knowledge of sequence variation across the complex. Highly duplicated and polymorphic regions of the human genome such as the MHC are, however, somewhat refractory to some whole-genome analysis methods. To address this issue, we are employing a bacterial artificial chromosome (BAC) cloning strategy to sequence entire MHC haplotypes from consanguineous cell lines as part of the MHC Haplotype Project. Here we present 4.25 Mb of the human haplotype QBL (HLA-A26-B18-Cw5-DR3-DQ2) and compare it with the MHC reference haplotype and with a second haplotype, COX (HLA-A1-B8-Cw7-DR3-DQ2), that shares the same HLA-DRB1, -DQA1, and -DQB1 alleles. We have defined the complete gene, splice variant, and sequence variation contents of all three haplotypes, comprising over 259 annotated loci and over 20,000 single nucleotide polymorphisms (SNPs). Certain coding sequences vary significantly between different haplotypes, making them candidates for functional and disease-association studies. Analysis of the two DR3 haplotypes allowed delineation of the shared sequence between two HLA class II–related haplotypes differing in disease associations and the identification of at least one of the sites that mediated the original recombination event. The levels of variation across the MHC were similar to those seen for other HLA-disparate haplotypes, except for a 158-kb segment that contained the HLA-DRB1, -DQA1, and -DQB1 genes and showed very limited polymorphism compatible with identity-by-descent and relatively recent common ancestry (<3,400 generations). These results indicate that the differential disease associations of these two DR3 haplotypes are due to sequence variation outside this central 158-kb segment, and that shuffling of ancestral blocks via recombination is a potential mechanism whereby certain DR–DQ allelic combinations, which presumably have favoured immunological functions, can spread across haplotypes and populations

Reconstruction and Validation of RefRec: A Global Model for the Yeast Molecular Interaction Network

Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is ∼67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in ∼590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format

Measures and Limits of Models of Fixation Selection

Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure) and the KL-divergence (a distance measure of probability distributions) combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection . We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced

Parallel use of shake flask and microtiter plate online measuring devices (RAMOS and BioLector) reduces the number of experiments in laboratory-scale stirred tank bioreactors

Background Conventional experiments in small scale are often performed in a Black Box fashion, analyzing only the product concentration in the final sample. Online monitoring of relevant process characteristics and parameters such as substrate limitation, product inhibition and oxygen supply is lacking. Therefore, fully equipped laboratory-scale stirred tank bioreactors are hitherto required for detailed studies of new microbial systems. However, they are too spacious, laborious and expensive to be operated in larger number in parallel. Thus, the aim of this study is to present a new experimental approach to obtain dense quantitative process information by parallel use of two small-scale culture systems with online monitoring capabilities: Respiration Activity MOnitoring System (RAMOS) and the BioLector device. Results The same mastermix (medium plus microorganisms) was distributed to the different small-scale culture systems: 1) RAMOS device; 2) 48-well microtiter plate for BioLector device; and 3) separate shake flasks or microtiter plates for offline sampling. By adjusting the same maximum oxygen transfer capacity (OTRmax), the results from the RAMOS and BioLector online monitoring systems supplemented each other very well for all studied microbial systems (E. coli, G. oxydans, K. lactis) and culture conditions (oxygen limitation, diauxic growth, auto-induction, buffer effects). Conclusions The parallel use of RAMOS and BioLector devices is a suitable and fast approach to gain comprehensive quantitative data about growth and production behavior of the evaluated microorganisms. These acquired data largely reduce the necessary number of experiments in laboratory-scale stirred tank bioreactors for basic process development. Thus, much more quantitative information is obtained in parallel in shorter time.Cluster of Excellence “Tailor-Made Fuels from Biomass”, which is funded by the Excellence Initiative by the German federal and state governments to promote science and research at German universities

Genome-Wide Data-Mining of Candidate Human Splice Translational Efficiency Polymorphisms (STEPs) and an Online Database

Variation in pre-mRNA splicing is common and in some cases caused by genetic variants in intronic splicing motifs. Recent studies into the insulin gene (INS) discovered a polymorphism in a 5' non-coding intron that influences the likelihood of intron retention in the final mRNA, extending the 5' untranslated region and maintaining protein quality. Retention was also associated with increased insulin levels, suggesting that such variants--splice translational efficiency polymorphisms (STEPs)--may relate to disease phenotypes through differential protein expression. We set out to explore the prevalence of STEPs in the human genome and validate this new category of protein quantitative trait loci (pQTL) using publicly available data.Gene transcript and variant data were collected and mined for candidate STEPs in motif regions. Sequences from transcripts containing potential STEPs were analysed for evidence of splice site recognition and an effect in expressed sequence tags (ESTs). 16 publicly released genome-wide association data sets of common diseases were searched for association to candidate polymorphisms with HapMap frequency data. Our study found 3324 candidate STEPs lying in motif sequences of 5' non-coding introns and further mining revealed 170 with transcript evidence of intron retention. 21 potential STEPs had EST evidence of intron retention or exon extension, as well as population frequency data for comparison.Results suggest that the insulin STEP was not a unique example and that many STEPs may occur genome-wide with potentially causal effects in complex disease. An online database of STEPs is freely accessible at http://dbstep.genes.org.uk/

Variation analysis and gene annotation of eight MHC haplotypes: The MHC Haplotype Project

The human major histocompatibility complex (MHC) is contained within about 4 Mb on the short arm of chromosome 6 and is recognised as the most variable region in the human genome. The primary aim of the MHC Haplotype Project was to provide a comprehensively annotated reference sequence of a single, human leukocyte antigen-homozygous MHC haplotype and to use it as a basis against which variations could be assessed from seven other similarly homozygous cell lines, representative of the most common MHC haplotypes in the European population. Comparison of the haplotype sequences, including four haplotypes not previously analysed, resulted in the identification of >44,000 variations, both substitutions and indels (insertions and deletions), which have been submitted to the dbSNP database. The gene annotation uncovered haplotype-specific differences and confirmed the presence of more than 300 loci, including over 160 protein-coding genes. Combined analysis of the variation and annotation datasets revealed 122 gene loci with coding substitutions of which 97 were non-synonymous. The haplotype (A3-B7-DR15; PGF cell line) designated as the new MHC reference sequence, has been incorporated into the human genome assembly (NCBI35 and subsequent builds), and constitutes the largest single-haplotype sequence of the human genome to date. The extensive variation and annotation data derived from the analysis of seven further haplotypes have been made publicly available and provide a framework and resource for future association studies of all MHC-associated diseases and transplant medicine

Both Positive and Negative Selection Pressures Contribute to the Polymorphism Pattern of the Duplicated Human CYP21A2 Gene.

The human steroid 21-hydroxylase gene (CYP21A2) participates in cortisol and aldosterone biosynthesis, and resides together with its paralogous (duplicated) pseudogene in a multiallelic copy number variation (CNV), called RCCX CNV. Concerted evolution caused by non-allelic gene conversion has been described in great ape CYP21 genes, and the same conversion activity is responsible for a serious genetic disorder of CYP21A2, congenital adrenal hyperplasia (CAH). In the current study, 33 CYP21A2 haplotype variants encoding 6 protein variants were determined from a European population. CYP21A2 was shown to be one of the most diverse human genes (HHe=0.949), but the diversity of intron 2 was greater still. Contrary to previous findings, the evolution of intron 2 did not follow concerted evolution, although the remaining part of the gene did. Fixed sites (different fixed alleles of sites in human CYP21 paralogues) significantly accumulated in intron 2, indicating that the excess of fixed sites was connected to the lack of effective non-allelic conversion and concerted evolution. Furthermore, positive selection was presumably focused on intron 2, and possibly associated with the previous genetic features. However, the positive selection detected by several neutrality tests was discerned along the whole gene. In addition, the clear signature of negative selection was observed in the coding sequence. The maintenance of the CYP21 enzyme function is critical, and could lead to negative selection, whereas the presumed gene regulation altering steroid hormone levels via intron 2 might help fast adaptation, which broadly characterizes the genes of human CNVs responding to the environment