Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable

<p>Abstract</p> <p>Background</p> <p>By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or those folding to poorly- or non-designable conformations.</p> <p>Results</p> <p>First, we generate all possible compact lattice conformations for the specified shape (a hexagon or a triangle) on the 2D triangular lattice. Then we generate all possible binary hydrophobic/polar (H/P) sequences and by using a specified energy function, thread them through all of these compact conformations. If for a given sequence the lowest energy is obtained for a particular lattice conformation we assume that this sequence folds to that conformation. Highly-designable conformations have many H/P sequences folding to them, while poorly-designable conformations have few or no H/P sequences. We classify sequences as folding to either highly – or poorly-designable conformations. We have randomly selected subsets of the sequences belonging to highly-designable and poorly-designable conformations and used them to train several different standard machine learning algorithms.</p> <p>Conclusion</p> <p>By using these machine learning algorithms with ten-fold cross-validation we are able to classify the two classes of sequences with high accuracy – in some cases exceeding 95%.</p

Recurrent Signature Patterns in HIV-1 B Clade Envelope Glycoproteins Associated with either Early or Chronic Infections

Here we have identified HIV-1 B clade Envelope (Env) amino acid signatures from early in infection that may be favored at transmission, as well as patterns of recurrent mutation in chronic infection that may reflect common pathways of immune evasion. To accomplish this, we compared thousands of sequences derived by single genome amplification from several hundred individuals that were sampled either early in infection or were chronically infected. Samples were divided at the outset into hypothesis-forming and validation sets, and we used phylogenetically corrected statistical strategies to identify signatures, systematically scanning all of Env. Signatures included single amino acids, glycosylation motifs, and multi-site patterns based on functional or structural groupings of amino acids. We identified signatures near the CCR5 co-receptor-binding region, near the CD4 binding site, and in the signal peptide and cytoplasmic domain, which may influence Env expression and processing. Two signatures patterns associated with transmission were particularly interesting. The first was the most statistically robust signature, located in position 12 in the signal peptide. The second was the loss of an N-linked glycosylation site at positions 413–415; the presence of this site has been recently found to be associated with escape from potent and broad neutralizing antibodies, consistent with enabling a common pathway for immune escape during chronic infection. Its recurrent loss in early infection suggests it may impact fitness at the time of transmission or during early viral expansion. The signature patterns we identified implicate Env expression levels in selection at viral transmission or in early expansion, and suggest that immune evasion patterns that recur in many individuals during chronic infection when antibodies are present can be selected against when the infection is being established prior to the adaptive immune response

Respiratory response of the deep-sea amphipod Stephonyx biscayensis indicates bathymetric range limitation by temperature and hydrostatic pressure

Depth zonation of fauna on continental margins is well documented. Whilst increasing hydrostatic pressure with depth has long been considered a factor contributing significantly to this pattern, discussion of the relative significance of decreasing temperature with depth has continued. This study investigates the physiological tolerances of fed and starved specimens of the bathyal lysianassoid amphipod Stephonyx biscayensis at varying temperature to acute pressure exposure by measuring the rate of oxygen consumption. Acclimation to atmospheric pressure is shown to have no significant interaction with temperature and/or pressure effects. Similarly, starvation is shown to have no significant effect on the interaction of temperature and pressure. Subsequently, the effect of pressure on respiration rate is revealed to be dependent on temperature: pressure equivalent to 2000 m depth was tolerated at 1 and 3°C; pressure equivalent to 2500 m depth was tolerated at 5.5°C; at 10°C pressure equivalent to 3000 m depth was tolerated. The variation in tolerance is consistent with the natural distribution range reported for this species. There are clear implications for hypotheses relating to the observed phenomenon of a biodiversity bottleneck between 2000 and 3000 metres, and for the potential for bathymetric range shifts in response to global climate change

Predicting Partner HIV Testing and Counseling Following a Partner Notification Intervention

Provider-assisted methods of partner notification increase testing and counseling among sexual partners of patients diagnosed with HIV, however they are resource-intensive. The sexual partners of individuals enrolled in a clinical trial comparing different methods of HIV partner notification were analyzed to identify who was unlikely to seek testing on their own. Unconditional logistic regression was used to identify partnership characteristics, which were assigned a score based on their coefficient in the final model, and a risk score was calculated for each participant. The risk score included male partner sex, relationship duration 6–24 months, and index education > primary. A risk score of ≥ 2 had a sensitivity of 68% and specificity of 78% in identifying partners unlikely to seek testing on their own. A risk score to target partner notification can reduce the resources required to locate all partners in the community while increasing the testing yield compared to patient-referral