Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy

BACKGROUND: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have been developed for predicting potential effects of amino acid substitutions using sequence, three-dimensional structural, and evolutionary properties of proteins, the applications are limited by the complication of the features and the availability of protein structural information. Another limitation is that the prediction results are hard to be interpreted with physicochemical principles and biological knowledge. RESULTS: To overcome these limitations, we proposed a novel feature set using physicochemical properties of amino acids, evolutionary profiles of proteins, and protein sequence information. We applied the support vector machine and the random forest with the feature set to experimental amino acid substitutions occurring in the E. coli lac repressor and the bacteriophage T4 lysozyme, as well as to annotated amino acid substitutions occurring in a wide range of human proteins. The results showed that the proposed feature set was superior to the existing ones. To explore physicochemical principles behind amino acid substitutions, we designed a simulated annealing bump hunting strategy to automatically extract interpretable rules for amino acid substitutions. We applied the strategy to annotated human amino acid substitutions and successfully extracted several rules which were either consistent with current biological knowledge or providing new insights for the understanding of amino acid substitutions. When applied to unclassified data, these rules could cover a large portion of samples, and most of the covered samples showed good agreement with predictions made by either the support vector machine or the random forest. CONCLUSION: The prediction methods using the proposed feature set can achieve larger AUC (the area under the ROC curve), smaller BER (the balanced error rate), and larger MCC (the Matthews' correlation coefficient) than those using the published feature sets, suggesting that our feature set is superior to the existing ones. The rules extracted by the simulated annealing bump hunting strategy have comparable coverage and accuracy but much better interpretability as those extracted by the patient rule induction method (PRIM), revealing that the strategy is more effective in inducing interpretable rules

Resummation of Jet Mass at Hadron Colliders

A method is developed for calculating the jet mass distribution at hadron colliders using an expansion about the kinematic threshold. In particular, we consider the mass distribution of jets of size R produced in association with a hard photon at the Large Hadron Collider. Expanding around the kinematic threshold, where all the energy goes into the jet and the photon, provides a clean factorization formula and allows for the resummation of logarithms associated with soft and collinear divergences. All of the large logarithms of jet mass are resummed at next-to-leading logarithmic level, and all the global logarithms at next-to-next-to-leading logarithmic level. A key step in the derivation is the factorization of the soft function into pieces associated with single scales and a remainder which contains nonglobal structure. This step, which is standard in traditional resummation, is implemented in effective field theory which is then used to resum the large logarithms using the renormalization group in a systematically improvable manner.Physic

The relationship between velocity utilization rate and pole vault performance

In the pole vault event, the velocity of approach is a highly vital factor. As velocity of approach improvements highly impact performance improvements. This study analysed the relationships between sprint running’s speed (SR), pole running (PR, without jump), and the pole vault approach (PVA, with real jump). Analysed too were the relationships between both the approach and performance’s respective running distance, velocity, and velocity utilization rates. Methods: Ten male pole vaulters were recruited. Measured was each 5-meter segment’s average velocity of his respective SR, PR, and PVA, along with the distance to maximum velocity. Results: The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with pole vault (PV) performance; The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with the last 5m PVA average velocity; The PVA velocity’s utilization rate was significantly negatively correlated with the difference between the distance to the PR’s maximum velocity and the PVA’s distance. Conclusion: The PR segment’s maximum speed capability can evaluate both a pole vaulter’s potential and pole vault-specific abilities. This study’s recruited pole vaulters’ respective approach distances were generally insufficient that resulted in a lower velocity utilization rate. Suggested is that in training, the pole vaulter could first find the distance required to reach the highest velocity upon starting from the PR test. Thus, this subsequently known distance could be applied in tandem with the pole vault’s approach to both improve the PVA’s utilization rate and reach the individual highest speed level

Prioritizing disease candidate genes by a gene interconnectedness-based approach

<p>Abstract</p> <p>Background</p> <p>Genome-wide disease-gene finding approaches may sometimes provide us with a long list of candidate genes. Since using pure experimental approaches to verify all candidates could be expensive, a number of network-based methods have been developed to prioritize candidates. Such tools usually have a set of parameters pre-trained using available network data. This means that re-training network-based tools may be required when existing biological networks are updated or when networks from different sources are to be tried.</p> <p>Results</p> <p>We developed a parameter-free method, interconnectedness (ICN), to rank candidate genes by assessing the closeness of them to known disease genes in a network. ICN was tested using 1,993 known disease-gene associations and achieved a success rate of ~44% using a protein-protein interaction network under a test scenario of simulated linkage analysis. This performance is comparable with those of other well-known methods and ICN outperforms other methods when a candidate disease gene is not directly linked to known disease genes in a network. Interestingly, we show that a combined scoring strategy could enable ICN to achieve an even better performance (~50%) than other methods used alone.</p> <p>Conclusions</p> <p>ICN, a user-friendly method, can well complement other network-based methods in the context of prioritizing candidate disease genes.</p

Rational application of fructose-1,6-diphosphate: From the perspective of pharmacokinetics

Fructose-1,6-diphosphate (FDP), a glycolytic metabolite, has been reported to protect susceptible organs during hypoxia or ischemia. However, there is paucity of human data on its pharmacokinetics after being exogenously administered. In the current study, the preliminary pharmacokinetics of FDP given orally to humans was investigated, and no typical peak was observed in the serum drug-time curve. Then, the pharmacokinetic studies were performed following multiple doses of of FDP in rats, and the Caco-2 monolayer model was used to study the absorption of FDP in vitro. The results suggested that plasma FDP concentration was significantly increased after oral multiple doses of 180 mg kg-1 but not 90 mg kg-1 of FDP, and FDP was partly depleted during the absorption, which was supposed to be consumed by the intestinal epithelium cells. Thus, we conclude that a high dose of FDP should be orally administered in order to get an effective plasma level

Resummation of Jet Mass at Hadron Colliders

A method is developed for calculating the jet mass distribution at hadron colliders using an expansion about the kinematic threshold. In particular, we consider the mass distribution of jets of size R produced in association with a hard photon at the Large Hadron Collider. Expanding around the kinematic threshold, where all the energy goes into the jet and the photon, provides a clean factorization formula and allows for the resummation of logarithms associated with soft and collinear divergences. All of the large logarithms of jet mass are resummed at next-to-leading logarithmic level (NLL), and all the global logarithms at next-to-next-to-leading logarithmic level (NNLL). A key step in the derivation is the factorization of the soft function into pieces associated with single scales and a remainder which contains non-global structure. This step, which is standard in traditional resummation, is implemented in effective field theory which is then used to resum the large logarithms using the renormalization group in a systematically improvable manner.Comment: 28 pages; 13 figure

What Differs on the Enzymatic Acetylation Mechanisms for Arylamines and Arylhydrazines Substrates? A Theoretical Study

The acetylation mechanisms of several selected typical substrates from experiments, including arylamines and arylhydrazines, are investigated with the density functional theory in this paper. The results indicate that all the transition states are characterized by a four-membered ring structure, and hydralazine (HDZ) is the most potent substrate. The bioactivity for all the compounds is increased in a sequence of PABA ≈ 4-AS < 4-MA < 5-AS ≈ INH < HDZ. The conjunction effect and the delocalization of the lone pairs of N atom play a key role in the reaction. All the results are consistent with the experimental data