Given the task definition, example input & output, solve the new input case.
In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Example: Alterations of the architecture of cerebral white matter in the developing human brain can affect cortical development and result in functional disabilities. A line scan diffusion-weighted magnetic resonance imaging (MRI) sequence with diffusion tensor analysis was applied to measure the apparent diffusion coefficient, to calculate relative anisotropy, and to delineate three-dimensional fiber architecture in cerebral white matter in preterm (n = 17) and full-term infants (n = 7). To assess effects of prematurity on cerebral white matter development, early gestation preterm infants (n = 10) were studied a second time at term. In the central white matter the mean apparent diffusion coefficient at 28 wk was high, 1.8 microm2/ms, and decreased toward term to 1.2 microm2/ms. In the posterior limb of the internal capsule, the mean apparent diffusion coefficients at both times were similar (1.2 versus 1.1 microm2/ms). Relative anisotropy was higher the closer birth was to term with greater absolute values in the internal capsule than in the central white matter. Preterm infants at term showed higher mean diffusion coefficients in the central white matter (1.4 +/- 0.24 versus 1.15 +/- 0.09 microm2/ms, p = 0.016) and lower relative anisotropy in both areas compared with full-term infants (white matter, 10.9 +/- 0.6 versus 22.9 +/- 3.0%, p = 0.001; internal capsule, 24.0 +/- 4.44 versus 33.1 +/- 0.6% p = 0.006). Nonmyelinated fibers in the corpus callosum were visible by diffusion tensor MRI as early as 28 wk; full-term and preterm infants at term showed marked differences in white matter fiber organization. The data indicate that quantitative assessment of water diffusion by diffusion tensor MRI provides insight into microstructural development in cerebral white matter in living infants.
Output: Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging.
This title is appropriate for the given abstract because the focus of this abstract is cerebral white matter assesment.

New input case for you: The FASTA package of sequence comparison programs has been modified to provide accurate statistical estimates for local sequence similarity scores with gaps. These estimates are derived using the extreme value distribution from the mean and variance of the local similarity scores of unrelated sequences after the scores have been corrected for the expected effect of library sequence length. This approach allows accurate estimates to be calculated for both FASTA and Smith-Waterman similarity scores for protein/protein, DNA/DNA, and protein/translated-DNA comparisons. The accuracy of the statistical estimates is summarized for 54 protein families using FASTA and Smith-Waterman scores. Probability estimates calculated from the distribution of similarity scores are generally conservative, as are probabilities calculated using the Altschul-Gish lambda, kappa, and eta parameters. The performance of several alternative methods for correcting similarity scores for library-sequence length was evaluated using 54 protein superfamilies from the PIR39 database and 110 protein families from the Prosite/SwissProt rel. 34 database. Both regression-scaled and Altschul-Gish scaled scores perform significantly better than unscaled Smith-Waterman or FASTA similarity scores. When the Prosite/ SwissProt test set is used, regression-scaled scores perform slightly better; when the PIR database is used, Altschul-Gish scaled scores perform best. Thus, length-corrected similarity scores improve the sensitivity of database searches. Statistical parameters that are derived from the distribution of similarity scores from the thousands of unrelated sequences typically encountered in a database search provide accurate estimates of statistical significance that can be used to infer sequence homology.
Output:
Empirical statistical estimates for sequence similarity searches