Methods in molecular biology
-
Multiple sequence alignment (MSA) is a fundamental and ubiquitous technique in bioinformatics used to infer related residues among biological sequences. Thus alignment accuracy is crucial to a vast range of analyses, often in ways difficult to assess in those analyses. ⋯ We outline a set of desirable characteristics for effective benchmarking, and evaluate each strategy in light of them. We conclude that there is currently no universally applicable means of benchmarking MSA, and that developers and users of alignment tools should base their choice of benchmark depending on the context of application-with a keen awareness of the assumptions underlying each benchmarking strategy.
-
Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry that offers the best prediction of the phenotype and the nature of a disease. Mass spectrometry now allows thousands of metabolites to be quantitated. ⋯ These sophisticated statistical techniques are computationally intensive. This chapter reviews techniques applicable to metabolomics approaches to disease.
-
Targeted intrathecal (IT) drug delivery systems (IDDS) are an option in algorithms for the treatment of patients with moderate to severe chronic refractory pain when more conservative options fail. This therapy is well established and supported by several publications. ⋯ Recent technological advances, new therapeutic applications, reported complications, and the costs as well as maintenance required for this therapy require the need to stay up-to-date about new recommendations that may improve outcomes. This chapter reviews all technological issues regarding IDDS implantation with follow-up, and pharmacological recommendations published during recent years that provide evidence-based decision making process in the management of chronic pain and spasticity in patients.
-
The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. ⋯ Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.
-
The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems have evolved as an adaptive surveillance and defense mechanism in bacteria and archaea that uses short RNAs to direct degradation of foreign genetic elements. Here, we present our protocol for utilizing the S. pyogenes type II bacterial CRISPR system to achieve sequence-specific genome alterations in human cells. ⋯ Genomic alterations at the target site are then introduced either through nonhomologous end joining (NHEJ) or through homologous recombination (HR) in the presence of an appropriate donor sequence. This RNA-guided editing tool offers greater ease of customization and synthesis in comparison to existing sequence-specific endonucleases and promises to become a highly versatile and multiplexable human genome engineering platform.