An integrated bioinformatics and computational biology approach identifies new BH3-only protein candidates

FoxD4L1 is a forkhead transcription factor that expands the neural ectoderm by down-regulating genes that promote the onset of neural differentiation and up-regulating genes that maintain proliferative neural precursors in an immature state. We previously demonstrated that binding of Grg4 to an Eh-1 motif enhances the ability of FoxD4L1 to down-regulate target neural genes but does not account for all of its repressive activity. Herein we analyzed the protein sequence for additional interaction motifs and secondary structure. Eight conserved motifs were identified in the C-terminal region of fish and frog proteins. Extending the analysis to mammals identified a high scoring motif downstream of the Eh-1 domain that contains a tryptophan residue implicated in protein-protein interactions. In addition, secondary structure prediction programs predicted an α-helical structure overlapping with amphibian-specific Motif 6 inXenopus, and similarly located α-helical structures in other vertebrate FoxD proteins. We tested functionality of this site by inducing a glutamine-to-proline substitution expected to break the predicted α-helical structure; this significantly reduced FoxD4L1’s ability to repress zic3and irx1. Because this mutation does not interfere with Grg4 binding, these results demonstrate that at least two regions, the Eh-1 motif and a more C-terminal predicted α-helical/Motif 6 site, additively contribute to repression. In the N-terminal region we previously identified a 14 amino acid motif that is required for the up-regulation of target genes. Secondary structure prediction programs predicted a short β-strand separating two acidic domains. Mutant constructs show that the β-strand itself is not required for transcriptional activation. Instead, activation depends upon a glycine residue that is predicted to provide sufficient flexibility to bring the two acidic domains into close proximity. These results identify conserved predicted motifs with secondary structures that enable FoxD4L1 to carry out its essential functions as both a transcriptional repressor and activator of neural genes

Estimate haplotype frequencies in pedigrees

BACKGROUND: Haplotype analysis has gained increasing attention in the context of association studies of disease genes and drug responsivities over the last years. The potential use of haplotypes has led to the initiation of the HapMap project which is to investigate haplotype patterns in the human genome in different populations. Haplotype inference and frequency estimation are essential components of this endeavour. RESULTS: We present a two-stage method to estimate haplotype frequencies in pedigrees, which includes haplotyping stage and estimation stage. In the haplotyping stage, we propose a linear time algorithm to determine all zero-recombinant haplotype configurations for each pedigree. In the estimation stage, we use the expectation-maximization (EM) algorithm to estimate haplotype frequencies based on these haplotype configurations. The experiments demonstrate that our method runs much faster and gives more credible estimates than other popular haplotype analysis software that discards the pedigree information. CONCLUSION: Our method suggests that pedigree information is of great importance in haplotype analysis. It can be used to speedup estimation process, and to improve estimation accuracy as well. The result also demonstrates that the whole haplotype configuration space can be substituted by the space of zero-recombinant haplotype configurations in haplotype frequency estimation, especially when the considered haplotype block is relatively short

PaTeCon: A Pattern-Based Temporal Constraint Mining Method for Conflict Detection on Knowledge Graphs

Temporal facts, the facts for characterizing events that hold in specific time periods, are attracting rising attention in the knowledge graph (KG) research communities. In terms of quality management, the introduction of time restrictions brings new challenges to maintaining the temporal consistency of KGs and detecting potential temporal conflicts. Previous studies rely on manually enumerated temporal constraints to detect conflicts, which are labor-intensive and may have granularity issues. We start from the common pattern of temporal facts and constraints and propose a pattern-based temporal constraint mining method, PaTeCon. PaTeCon uses automatically determined graph patterns and their relevant statistical information over the given KG instead of human experts to generate time constraints. Specifically, PaTeCon dynamically attaches class restriction to candidate constraints according to their measuring scores.We evaluate PaTeCon on two large-scale datasets based on Wikidata and Freebase respectively. The experimental results show that pattern-based automatic constraint mining is powerful in generating valuable temporal constraints.Comment: Accepted by AAAI2

Automatic Rule Generation for Time Expression Normalization

The understanding of time expressions includes two sub-tasks: recognition and normalization. In recent years, significant progress has been made in the recognition of time expressions while research on normalization has lagged behind. Existing SOTA normalization methods highly rely on rules or grammars designed by experts, which limits their performance on emerging corpora, such as social media texts. In this paper, we model time expression normalization as a sequence of operations to construct the normalized temporal value, and we present a novel method called ARTime, which can automatically generate normalization rules from training data without expert interventions. Specifically, ARTime automatically captures possible operation sequences from annotated data and generates normalization rules on time expressions with common surface forms. The experimental results show that ARTime can significantly surpass SOTA methods on the Tweets benchmark, and achieves competitive results with existing expert-engineered rule methods on the TempEval-3 benchmark.Comment: Accepted to Findings of EMNLP 202

Bulk photovoltaic effect in two-dimensional ferroelectric semiconductor α\alpha-In2_2Se3_3

Bulk photovoltaic effect, which arises from crystal symmetry-driven charge carrier separation, is an intriguing physical phenomenon that has attracted extensive interest in photovoltaic application due to its junction-free photovoltaic and potential to surpass Shockley-Queisser limit. Whereas conventional ferroelectric materials mostly suffer from extremely low photocurrent density and weak photovoltaic response at visible light wavelengths. Emerging two-dimensional ferroelectric semiconductors with coupled visible light absorption and spontaneous polarization characteristics are a promising alternative for making functional photoferroelectrics. Herein, we report the experimental demonstration of the bulk photovoltaic effect behavior based on the 2D ferroelectric semiconductor {$\alpha$-InSe caused by an out-of-plane polarization induced depolarization field. The {$\alpha$-InSe device exhibits enhanced bulk photovoltaic response in the visible light spectrum owing to its narrow bandgap. It was demonstrated that the generated photovoltaic current density was nearly two orders of magnitude greater than conventional bulk ferroelectric materials. These findings highlight the potential of 2D ferroelectric semiconductor materials for bulk photovoltaic applications in a broad spectral region

Preparation and Characterization of Superhydrophobic Modification of Polyvinylidene Fluoride Membrane by Dip-Coating

The superhydrophobicity polyvinylidene fluoride (PVDF) membranes were modified via reducing surface energy by dip-coating perfluoroalkyl methacrylic copolymer (Zonyl 8740) onto the membranes prepared on mat glass. The chemical component of the unmodified and modified PVDF membranes surface was investigated by ATR-FTIR. Morphology and hydrophobicity of the unmodified and modified PVDF membranes were examined by scanning electronic microscopy and water contact angle, respectively. The effects of concentration of Zonyl 8740, coating time, conditions of heat treatment on hydrophobic capability of PVDF membranes were investigated. The results showed that the water contact angle increased from 141˚ to 151˚ by the dip-coating modification, therefore getting superhydrophobic PVDF membrane. Moreover, the porosity and the morphology of modified PVDF membrane were unchanged by the dip-coating modification. This results suggested that the hydrophobicty stability of the modified PVDF membrane was also good

Core Point Pixel-Level Localization by Fingerprint Features in Spatial Domain

Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve of ridges. The summit of this Curve is regarded as the localization result. Furthermore, an approach for removing false Furcation and Confluence based on their correlations is developed to enhance the method robustness. Experimental results show that the proposed method achieves satisfactory core localization accuracy in a large number of samples