<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def filter_enzyme_kinase(stmts_in, **kwargs):
 """Filter Phosphorylations to ones where the enzyme is a known kinase. Parameters stmts_in : list[indra.statements.Statement] A list of statements to filter. save : Optional[str] The name of a pickle file to save the results (stmts_out) into. Returns ------- stmts_out : list[indra.statements.Statement] A list of filtered statements. """

    logger.info('Filtering %d statements to remove ' % len(stmts_in) +
                'phosphorylation by non-kinases...')
    path = os.path.dirname(os.path.abspath(__file__))
    kinase_table = read_unicode_csv(path + '/../resources/kinases.tsv',
                                    delimiter='\t')
    gene_names = [lin[1] for lin in list(kinase_table)[1:]]
    stmts_out = []
    for st in stmts_in:
        if isinstance(st, Phosphorylation):
            if st.enz is not None:
                if st.enz.name in gene_names:
                    stmts_out.append(st)
        else:
            stmts_out.append(st)
    logger.info('%d statements after filter...' % len(stmts_out))
    dump_pkl = kwargs.get('save')
    if dump_pkl:
        dump_statements(stmts_out, dump_pkl)
    return stmts_out