Conditional random fields (CRFs) provide a powerful tool for structured prediction, but cast significant challenges in both the learning and inference steps. Approximation techniques are widely used in both steps, which should be considered jointly to guarantee good performance (a.k.a. “inferning"). Perturb-and-MAP models provide a promising alternative to CRFs, but require global combinatorial...

MOTIVATION Residue-residue contact prediction is important for protein structure prediction and other applications. However, the accuracy of current contact predictors often barely exceeds 20% on long-range contacts, falling short of the level required for ab initio structure prediction. RESULTS Here, we develop a novel machine learning approach for contact map prediction using three steps of...

Data were provided by the United States Geological Survey on selenium concentrations collected over Benton Lake National Wildlife Refuge near Great Falls, Montana. High selenium concentrations are known to decrease reproduction rates in lake waterfowl (USFWS, 2012, p. 204). Previous work in sediment selenium data included mean concentration estimates and comparisons using several variance estim...

MAP Structured Output Prediction by Sampling Shankar Vembu, Thomas Gärtner, and Mario Boley [email protected] Fraunhofer IAIS, Schloß Birlinghoven, 53754 Sankt Augustin, Germany We consider maximum a posteriori parameter estimation for structured output prediction with exponential family models. In this setting the main difficulty lies in the computation of the partition fun...

This supplement includes brief elaborations on the main paper that may be of interest to some readers. In Section 1, we explain the minorization procedure underlying MAP inference. In Section 2, we lay out the details of our stochastic subgradient approximation procedure for online MAP inference. In Section 3, we lay out a useful interpretation of MAP prediction. In Section 4, we summarize the ...

Wireless Sensor Networks can be used to monitor the physical phenomenon in such areas where human approach is nearly impossible. Hence the limited power supply is the major constraint of the WSNs due to the use of non-rechargeable batteries in sensor nodes. A lot of researches are going on to reduce the energy consumption of sensor nodes. Energy map can be used with clustering, data disseminati...

Predicting protein structure from sequence remains a major open problem in protein biochemistry. One component of predicting complete structures is the prediction of inter-residue contact patterns (contact maps). Here, we discuss protein contact map prediction by machine learning. We describe a novel method for contact map prediction that uses the evolution of logic circuits. These logic circui...

The prediction of protein structures is a current issue of great significance in structural bioinformatics. More specifically, the prediction of the tertiary structure of a protein consists of determining its three-dimensional conformation based solely on its amino acid sequence. This study proposes a method in which protein fragments are assembled according to their physicochemical similaritie...

Electron cryo-microscopy (cryo-EM) is an experimental technique to determine the 3-dimensional structure for large protein complexes. Currently this technique is able to generate protein density maps at 6 to 9 Å resolution. Although secondary structures such as α-helix and β-sheet can be visualized from these maps, there is no mature approach to deduce their tertiary topology, the linear order ...