ALBERT

Description: Motivation: Computational prediction of compound–protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods. Results: This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein–protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans . We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new interactions by training an support vector machine classifier on the positive interactions annotated in DrugBank and our screened negative interactions. The screened negative samples and the predicted interactions provide the research community with a useful resource for identifying new drug targets and a helpful supplement to the current curated compound–protein databases. Availability: Supplementary files are available at: http://admis.fudan.edu.cn/negative-cpi/ . Contact: sgzhou@fudan.edu.cn Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: The well-known Welch–Gong (WG) stream cipher, proposed by Nawaz and Gong in 2005, was submitted to the hardware profile of the eSTREAM project. In the last several years, the original WG has come under several cryptanalytic attacks. However, as for the final version of WG, no attack has been published on it until now. In this paper, an efficient key recovery attack on the final WG stream cipher in the related key setting is proposed. Under related keys, we can recover the 128-bit secret key of WG-128 with a time complexity of $2^{89}$ and a memory complexity of $2^{45}$ . The success probability of the attack is 0.6321. This result shows that our attack on WG-128 is much better than an exhaustive key search in the related key setting. Furthermore, our cryptanalytic results show that WG with IV size no less than 80 bits is vulnerable to a related key attack. The main feature of our attack is that it is independent of the number of steps in the key/IV setup of WG, and then increasing the number of steps in the key/IV setup cannot strengthen the resistance of WG against a related key attack. Finally, a recommended approach to repair the weakness and strengthen the resistance of WG against a related key attack is presented.

Description: Accumulating evidence indicates that microRNAs (miRNAs) can function as oncogenes or tumor suppressor genes by controlling few key targets, which in turn contribute to the pathogenesis of cancer. The identification of cancer-related key miRNA–target interactions remains a challenge. We performed a systematic analysis of known cancer-related key interactions manually curated from published papers based on different aspects including sequence, expression and function. Known cancer-related key interactions show more miRNA binding sites (especially for 8mer binding sites), more reliable binding of miRNA to the target region, higher expression associations and broader functional coverage when compared to non-disease-related interactions. Through integrating these sequence, expression and function features, we proposed a bioinformatics approach termed PCmtI to prioritize cancer-related key interactions. Ten-fold cross-validation of our approach revealed that it can achieve an area under the receiver operating characteristic curve of 93.9%. Subsequent leave-one-miRNA-out cross-validation also demonstrated the performance of our approach. Using miR-155 as a case, we found that the top ranked interactions can account for most functions of miR-155. In addition, we further demonstrated the power of our approach by 23 recently identified cancer-related key interactions. The approach described here offers a new way for the discovery of novel cancer-related key miRNA–target interactions.

Description: Geography Markup Language (GML) has become a de facto standard for encoding and exchanging geographic data. Usually, GML documents are of huge size due to its verbose structures and textual data, hence it is very costly to store and transit them. In this paper, we propose an effective pattern-based approach to compressing GML documents. First, a tree-structured pattern from the GML document under compression is extracted. Then, a tree automaton for matching the document against the extracted pattern is constructed. While doing compression, the GML document is matched against the pattern to generate a bits-stream that represents the difference between the document's structure and the extracted pattern. Meanwhile, we separate document structure from document content and group document content into different streams according to the tags. Spatial coordinate data are compressed by delta encoding. Finally, the extracted pattern, all streams and encodings are forwarded to a text compressor gzip. Extensive experiments on real GML documents show that the proposed approach outperforms the existing XML and GML compression approaches in compression ratio, while keeping an acceptable compression efficiency.

Description: With the increase of available protein–protein interaction (PPI) data, more and more efforts have been put to PPI network modeling, and a number of models of PPI networks have been proposed. Roughly speaking, good models of PPI networks should be able to accurately describe PPI mechanisms, and thus reproduce the structures of PPI networks. With such models, theoretical and/or computational biologists can efficiently explore the evolution and dynamics of PPI networks. However, a theoretical and/or computational biologist may feel confused when she/he has to choose a proper PPI model for her/his research work from a dozen of candidate models, while there is no guideline available to help her/him. To tackle this problem, in this article, we carry out a comprehensive performance comparison study on 12 existing models over PPI datasets of four species (yeast, mouse, fruit fly and nematode), by comparing the global and local statistical properties of the original PPI networks and the model-reproduced ones. To draw more convincing conclusions, we use the mean reciprocal rank to combine the ranks of a certain model on all statistical properties. Our experimental results indicate that the PS_Seed model [Solé and Pastor-Satorras (PS) model with seed] the STICKY model and the DD_Seed model (Duplication-Divergence model with seed) fit best with the test PPI datasets. By analyzing the underlying mechanisms of the models with better fitting ability, our analysis shows that the evolutionary mechanism of node duplication and link dynamics and the mechanisms with ‘degree-weighted’ behaviors seem to be able to describe the PPI networks better.

Description: Polyadenylation [poly(A)] is a vital step in post-transcriptional processing of pre-mRNA. Alternative polyadenylation is a widespread mechanism of regulating gene expression in eukaryotes. Defining poly(A) sites contributes to the annotation of transcripts’ ends and the study of gene regulatory mechanisms. Here, we survey methods for collecting poly(A) sites using high-throughput sequencing technologies and summarize the general processes for genome-wide poly(A) site identifications. We also compare the performances of various poly(A) site prediction models and discuss the relationship between poly(A) site identification from sequencing projects and predictive modeling. Moreover, we attempt to address some potential problems in current researches and propose future directions related to polyadenylation research.

Description: Nucleosome positioning plays an essential role in cellular processes by modulating accessibility of DNA to proteins. Many computational models have been developed to predict genome-wide nucleosome positions from DNA sequences. Comparative analysis of predicted and experimental nucleosome positioning maps facilitates understanding the regulatory mechanisms of transcription and DNA replication. Therefore, a comprehensive evaluation of existing computational methods is important and useful for biologists to choose appropriate ones in their research. In this article, we carried out a performance comparison among eight widely used computational methods on four species including yeast, fruitfly, mouse and human. In particular, we compared these methods on different regions of each species such as gene sequences, promoters and 5'UTR exons. The experimental results show that the performances of the two latest versions of the thermodynamic model are relatively steadier than the other four methods. Moreover, these methods are workable on four species, but their performances decrease gradually from yeast to human, indicating that the fundamental mechanism of nucleosome positioning is conserved through the evolution process, but more and more factors participate in the determination of nucleosome positions, which leads to sophisticated regulation mechanisms.

Description: Loiss is a new byte-oriented stream cipher designed in 2010. It takes a 128-bit initial key and a 128-bit initial vector (IV) as inputs, and provides 128-bit-level security claimed by the designers. In this paper, we find a differential characteristic with significant probability over the full initialization of Loiss. Based on this differential characteristic, two differential key recovery attacks on Loiss are proposed. The first attack has a computational complexity of2 123.61 , requiring two related keys, 2 34.16 chosen IVs and 2 39.16 keystream bytes. The second attack is based on the first attack: reducing the computational complexity at the cost of increased data complexity. The second attack has a computational complexity of 2 64 , requiring two related keys, 2 36.26 chosen IVs and 2 41.26 keystream bytes. The result shows that our second attack is much better than a brute force attack, and then Loiss does not provide 128-bit-level security. Furthermore, a new proposal for the initialization of Loiss is proposed. The modified Loiss keeps the basic structure of Loiss and provides enough resistance against our attacks on the original Loiss. Based on our security analysis, we conjecture that no attacks lower than brute force are possible on the modified Loiss stream cipher.

Description: Based on Insight-HXMT data, we report on the pulse fraction evolution during the 2017–2018 outburst of the newly discovered first Galactic ultraluminous X-ray (ULX) source Swift J0243.6+6124. The pulse fractions of 19 observation pairs selected in the rising and fading phases with similar luminosity are investigated. The results show a general trend of the pulse fraction increasing with luminosity and energy at supercritical luminosity. However, the relative strength of the pulsation between each pair evolves strongly with luminosity. The pulse fraction in the rising phase is larger at luminosity below 7.71 × 1038 erg s−1, but smaller at above. A transition luminosity is found to be energy independent. Such a phenomenon is first confirmed by Insight-HXMT observations and we speculate that it may have relation with the radiation-pressure-dominated accretion disc.